Software | RP Name | Software Description | ✨AI Description | ✨Core Features | Software Documentation | ✨Software Type | ✨Research Area | ✨Research Discipline | ✨General Tags | Software's Web Page | ✨Research Field | Example Software Use | RP Software Documentation | Version Info | ✨Software Class | ✨Example Use |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7z | Ookami | 7-Zip is a file archiver with a high compression ratio. Description Source: https://www.7-zip.org/ |
7-Zip is a file archiver with a high compression ratio. It supports several archive formats and can be used to compress and decompress files efficiently. | 7-Zip provides a high compression ratio, supports various archive formats including 7z, XZ, BZIP2, GZIP, TAR, ZIP, and WIM, has a powerful file manager and command-line version, offers AES-256 encryption, and is open-source software. | https://www.7-zip.org/ | Archiver | General | General | File Archiver, Compression, Encryption | https://www.7-zip.org/ | https://www.youtube.com/watch?v=N48Z0nG0bcQ | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 22.01 | Utility | ||
abacas | Anvil | Abacas is a tool for algorithm based automatic contiguation of assembled sequences. | ABACAS is a tool for rapid bacterial genome contig assembly. It takes contigs produced by an assemblrer and scaffolds them to generate a pseudo-chromosome. It can handle multiple contigs and uses reference genomes for scaffolding. | Contig assembly, scaffolding, reference genome utilization | https://abacas.sourceforge.net/documentation.html | Genome Assembly | Genetics | Biological Sciences | Bacterial Genome, Genome Assembly | https://abacas.sourceforge.net/ | Biological Sciences | https://abacas.sourceforge.net/Manual.html | Anvil: https://www.rcac.purdue.edu/software/abacas | Anvil: 1.3.1 | Bioinformatics | |
abaqus | Expanse | Abaqus is a software suite for finite element analysis and computer-aided engineering, primarily used in engineering and design fields for simulating the behavior of structures and materials under various conditions. It offers advanced capabilities for modeling, analysis, and visualization, making it a powerful tool for solving complex engineering challenges. | Abaqus is a software suite used for finite element analysis and computer-aided engineering simulations for a wide range of industrial applications. It provides powerful simulation capabilities to analyze the behavior of materials and structures under various conditions. | Finite Element Analysis (Fea), Structural Analysis, Thermal Analysis, Fluid Analysis, Multiphysics Simulation, Explicit & Implicit Solvers, Material Modeling, Contact Analysis, Fatigue Analysis, Nonlinear Analysis | https://www.3ds.com/support/documentation/user-guides | Simulation Software | Engineering | Engineering & Technology | Simulation, Finite Element Analysis, Computer-Aided Engineering, Materials Analysis | https://www.3ds.com/products/simulia/abaqus | Engineering & Technology | https://www.3ds.com/products/simulia/training https://www.youtube.com/watch?v=3-NIKzmhxOU&list=PLz_XdUL-6Y_k-LgmCKo5ejqRAGpfXPk23 |
Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 2018.Bk, 2018, 2021Hf7 | Other | |
abinit | Bridges-2, Expanse, Faster | ABINIT is a software suite to calculate the optical, mechanical, vibrational, and other observable properties of materials. Starting from the quantum equations of density functional theory, you can build up to advanced applications with perturbation theories based on DFT, and many-body Green's functions (GW and DMFT). Description Source: https://www.abinit.org/ |
Abinit is a first-principles simulation software for materials science, condensed matter physics, and related fields. It performs electronic structure calculations based on density functional theory (DFT) and many-body perturbation theory. | Abinit offers a wide range of functionalities for modeling materials properties, such as electronic band structures, total energies, forces, dielectric properties, and more. It supports parallel computing for scalability and efficiency. | https://docs.abinit.org/tutorial/ | Electronic Structure Calculation | Materials Science | Condensed Matter Physics | Materials Science, Condensed Matter Physics, Electronic Structure Calculations | https://www.abinit.org/ | Physical Sciences | https://docs.abinit.org/tutorial/ | Bridges-2: https://www.psc.edu/resources/software/abinit Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Bridges-2: 9.4.2-Intel Expanse: Q47Zuuw Faster: 9.4.2, 9.6.2 |
Simulation Software | |
abismal | Anvil | Another Bisulfite Mapping Algorithm (abismal) is a read mapping program for bisulfite sequencing in DNA methylation studies. | AbInitio Solvers for Intersolute-interaction and Surfaces and Materials with Ab-initio Library | Abismal provides ab-initio solvers for studying intersolute-interaction and surfaces and materials. It includes a library for ab-initio calculations and supports various methods for electronic structure calculations. | https://github.com/smithlabcode/abismal/blob/master/docs/MANUAL.md | Computational Chemistry Software | Sciences | Biology | Ab-Initio, Electronic Structure Calculations, Materials Science | https://github.com/smithlabcode/abismal | Other Natural Sciences | Anvil: https://www.rcac.purdue.edu/software/abismal | Anvil: 3.0.0 | Scientific Computing Software | ||
abpoa | Anvil | abPOA is an extended version of Partial Order Alignment (POA) that performs adaptive banded dynamic programming (DP) with an SIMD implementation. abPOA can perform multiple sequence alignment (MSA) on a set of input sequences and generate a consensus sequence by applying the heaviest bundling algorithm to the final alignment graph. Description Source: https://github.com/yangao07/abPOA |
ABPOA (adaptive bi-path overlap aligner) is a multiple sequence alignment tool that employs a novel bi-path structure to generate pairwise alignments between sequences for constructing a multiple sequence alignment. It is designed to align long noisy read sequences efficiently and accurately by adapting to local alignment conditions. | 1. Utilizes a bi-path structure for pairwise sequence alignment\r 2. Designed for aligning long noisy read sequences\r 3. Adapts to local alignment conditions to improve accuracy\r 4. Efficient and scalable for handling large datasets |
https://github.com/yangao07/abPOA#general-usage | Alignment Tool | Comparative Genomics | Genetics | Multiple Sequence Alignment, Sequence Alignment, Long Read Sequences | https://github.com/yangao07/abPOA | Biological Sciences | https://github.com/yangao07/abPOA/blob/main/example.c https://github.com/yangao07/abPOA/blob/main/sub_example.c |
Anvil: https://www.rcac.purdue.edu/software/abpoa | Anvil: 1.4.1 | Bioinformatics | |
abricate | Anvil | Mass screening of contigs for antimicrobial resistance or virulence genes. It comes bundled with multiple databases: NCBI, CARD, ARG-ANNOT, Resfinder, MEGARES, EcOH, PlasmidFinder, Ecoli_VF and VFDB. | abricate is a tool for finding antimicrobial resistance and virulence genes in bacterial genomes. | Identify Antimicrobial Resistance Genes, Detect Virulence Genes, Analyze Bacterial Genomes | https://github.com/tseemann/abricate | Tool | Sciences | Biology | Antimicrobial Resistance, Genomic Analysis, Bacterial Genomics | https://github.com/tseemann/abricate | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/abricate | Anvil: 1.0.1 | Bioinformatics | ||
abseil | Aces, Faster | Abseil is an open source collection of C++ libraries drawn from the most fundamental pieces of Google’s internal codebase. These libraries are the nuts-and-bolts that underpin almost everything Google runs. Description Source: https://abseil.io/about/ |
Abseil is an open-source collection of C++ code (compliant to C++11) designed to augment the C++ standard library. It provides a set of high-quality library code that is well tested, portable, and efficient for a wide range of purposes. | 1. Cross-platform support\r 2. Robust and well-tested library code\r 3. Portable and efficient implementations\r 4. Compliant with C++11 standards\r 5. Designed to complement the C++ standard library |
https://abseil.io/docs/ | Code Library | General | General | C++ Library, Open Source, Cross-Platform | https://abseil.io/ | Computer & Information Sciences | https://abseil.io/docs/cpp/quickstart https://abseil.io/tips/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 20230125.2, 20230125.3, 20230802.1 Faster: 20210324.2, 20230125.2, 20230125.3, 20230802.1 |
Library | |
abyss | Anvil, Bridges-2, Faster | ABySS is a de novo, parallel, paired-end sequence assembler that is designed for short reads. The single-processor version is useful for assembling genomes up to 100 Mbases in size. The parallel version is implemented using MPI and is capable of assembling larger genomes. Description Source: https://www.bcgsc.ca/resources/software/abyss |
ABySS (Assembly By Short Sequences) is a de novo, parallel, paired-end sequence assembler that is designed for large genomes and also works well on smaller genomes. | ABySS can assemble very large genomes using paired-end sequencing data. It supports a wide range of input read lengths and allows users to specify the insert size of the library. ABySS is parallelized to run efficiently on High-Performance Computing (HPC) clusters. | https://github.com/bcgsc/abyss | Hpc Tool | Genetics | Biological Sciences | Assembly, De Novo Assembly, Sequence Assembler, Large Genomes | https://www.bcgsc.ca/resources/software/abyss | Biological Sciences | https://github.com/bcgsc/abyss?tab=readme-ov-file#assemble-a-small-synthetic-data-set | Anvil: https://www.rcac.purdue.edu/software/abyss Bridges-2: https://www.psc.edu/resources/software/abyss Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 2.3.2, 2.3.4 Bridges-2: 2.1.5 Faster: 2.1.5 |
Bioinformatics | |
accessusage | Expanse | Adds ACCESS accessusage tool to paths in the login shell environment. | https://software.xsede.org/production/accessusage/latest/INSTALL | Service | General | General | https://software.xsede.org/packaged-software/access-usage-accessusage | https://software.xsede.org/production/accessusage/latest/INSTALL_Testing | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 0.5-1 | Developer Support | |||||
actc | Aces, Anvil, Faster | ACTC is a graphics optimization tool that enhances the rendering efficiency of 3D models by restructuring their geometric data. It's particularly useful in applications using OpenGL and Direct3D, where it can significantly improve rendering speed and reduce computational load. Description Source: https://plunk.org/~grantham/public/actc/README |
ACTC (Assembly, Clustering, and Transformation for Connected Components) is a software tool for finding connected components in large, distributed graphs. It is specifically designed to handle massive graphs efficiently. | Identifying Connected Components In Large, Distributed Graphs, Efficient Handling Of Massive Graphs, Scalability | https://plunk.org/~grantham/public/actc/manual.html | Tool | General | Biology, Mathematics | Graph Analytics, Connected Components, Distributed Computing | https://plunk.org/~grantham/public/actc/ | Computer & Information Sciences | https://plunk.org/~grantham/public/actc/tcsample.c | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/actc Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.1 Anvil: 0.2.0 Faster: 1.1 |
Graph Analytics | |
adapterremoval | Anvil, Faster | AdapterRemoval searches for and removes adapter sequences from High-Throughput Sequencing (HTS) data and (optionally) trims low quality bases from the 3’ end of reads following adapter removal. AdapterRemoval can analyze both single end and paired end data, and can be used to merge overlapping paired-ended reads into (longer) consensus sequences. Additionally, AdapterRemoval can construct a consensus adapter sequence for paired-ended reads, if which this information is not available. | AdapterRemoval searches for and removes adapter sequences from High-Throughput Sequencing (HTS) data. AdapterRemoval can also identify paired sequences in which both reads overlap after adapter removal and generate a statistics file detailing the results. | Adapter Trimming & Removal, Identification Of Overlapping Paired-End Reads, Statistics Generation | https://adapterremoval.readthedocs.io/en/stable/ | Bioinformatics Tool | Sciences | Biology | Bioinformatics, Hts Data Processing, Sequence Analysis | https://github.com/MikkelSchubert/adapterremoval | Biological Sciences | https://adapterremoval.readthedocs.io/en/stable/examples.html | Anvil: https://www.rcac.purdue.edu/software/adapterremoval Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 2.3.3 Faster: 2.3.3 |
Sequence Analysis Tool | |
adios2 | Expanse | ADIOS2 is developed as part of the United States Department of Energy's Exascale Computing Project. It is a framework for scientific data I/O to publish and subscribe to data when and where required. ADIOS2 transports data as groups of self-describing variables and attributes across different media types (such as files, wide-area-networks, and remote direct memory access) using a common application programming interface for all transport modes. ADIOS2 can be used on supercomputers, cloud systems, and personal computers. | ADIOS 2 (Adaptable Input/Output System) is a next-generation high-performance I/O middleware library that provides a simple, high-level interface for efficiently managing data on parallel storage systems. It is designed to address the increasing challenges of achieving high performance and scalability when dealing with I/O operations in large-scale scientific simulations and data processing applications. | High-Performance I/O Middleware Library, Simple & High-Level Interface, Efficient Data Management On Parallel Storage Systems, Support For Various Data Formats & Storage Systems, Parallel I/O Operations For Large-Scale Simulations, Scalability & Performance Optimizations | https://adios2.readthedocs.io/en/v2.10.0/ | Library | Sciences | Computer Science | I/O Middleware, High-Performance Computing, Data Management, Parallel Computing | https://github.com/ornladios/ADIOS2 | Computer & Information Sciences | https://adios2.readthedocs.io/en/v2.10.0/tutorials/basicTutorials.html | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: F2Ejleg, M6X3V7O, ... | Middleware | |
adol-c | Expanse | ADOL-C is an operator overloading based AD-tool that allows to compute derivatives for functions given as C or C++ source code. ADOL-C can handle codes based on classes, templates and other advanced C++-features. The resulting derivative evaluation routines may be called from C, C++, Fortran, or any other language that can be linked with C. | ADOL-C (Automatic Differentiation by Overloading in C++) is a software package for the calculation of derivatives of given C or C++ code. It allows for the efficient calculation of first and higher derivative information, which is useful in optimization, sensitivity analysis, and uncertainty quantification. | Automatic Differentiation For C/C++ Code, Efficient Calculation Of Derivatives, Support For First & Higher Order Derivative Information, Useful For Optimization, Sensitivity Analysis, & Uncertainty Quantification | https://github.com/coin-or/ADOL-C/tree/master/ADOL-C/doc | Computational Software | Engineering | Mathematics | Automatic Differentiation, Computational Mathematics, Optimization, Sensitivity Analysis, Uncertainty Quantification | https://github.com/coin-or/ADOL-C | Mathematics | https://github.com/coin-or/ADOL-C/tree/master/ADOL-C/examples | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Hjqerr7, Qygdtvg, ... | Library | |
advisor | Kyric, Stampede3 | Intel Advisor is a performance analysis tool designed to help developers optimize and parallelize their software on Intel architectures. It provides insights for efficient vectorization, threading, and offloading to accelerators, aiding in achieving maximum performance from applications. | Advisor is a comprehensive software tool designed for optimizing HPC applications and maximizing performance on current and future HPC systems. It offers insights into performance bottlenecks, parallel patterns, and potential improvements. | Performance Optimization For Hpc Applications, Identifying Performance Bottlenecks, Analyzing Parallel Patterns, Recommendations For Performance Improvements | https://www.intel.com/content/www/us/en/docs/advisor/get-started-guide/2023-1/overview.html | Performance Optimization | Hpc, Performance Optimization, Parallel Computing | https://www.intel.com/content/www/us/en/developer/tools/oneapi/advisor.html | Engineering & Technology | Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ | Kyric: Latest, 2021.1.1 Stampede-3: 23.1, 24.0 |
Tool | ||||
advntr | Anvil | adVNTR is a tool for genotyping Variable Number Tandem Repeats (VNTR) from sequence data. It works with both NGS short reads (Illumina HiSeq) and SMRT reads (PacBio) and finds diploid repeating counts for VNTRs and identifies possible mutations in the VNTR sequences. | Advntr (Adaptive Variant Detection in NGS data with trained Recurrent Neural Networks) is a software tool that utilizes deep learning techniques to identify genetic variants in next-generation sequencing (NGS) data. It employs trained recurrent neural networks to accurately and efficiently detect variants in DNA sequences. | Utilizes Deep Learning Methods For Variant Detection, Trained Recurrent Neural Networks For Improved Accuracy, Works With Next-Generation Sequencing (Ngs) Data, Efficient & Fast Variant Detection Process | https://advntr.readthedocs.io/en/latest/index.html | Bioinformatics | Genomics | Genetics | Ngs, Variant Detection, Deep Learning, DNA Sequencing | https://github.com/mehrdadbakhtiari/adVNTR | Biological Sciences | https://advntr.readthedocs.io/en/latest/tutorial.html | Anvil: https://www.rcac.purdue.edu/software/advntr | Anvil: 1.4.0, 1.5.0 | Genetic Variant Analysis | |
aesara | Faster | Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. | Aesara is a Python library for symbolic mathematical operations, particularly focusing on deep learning and optimization. It allows for the creation of complex mathematical expressions and their manipulation symbolically, enabling automatic differentiation and optimization of functions. | Symbolic mathematical operations, automatic differentiation, optimization, deep learning support | https://aesara.readthedocs.io/en/latest/ | Library | Engineering | Mathematics | Python Library, Symbolic Computation, Deep Learning, Optimization | https://github.com/aesara-devs/aesara | Computer & Information Sciences | https://aesara.readthedocs.io/en/latest/reference/index.html | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.8.9 | Scientific Computing | |
aflow | Faster | AFLOW is a comprehensive software framework for autonomous density functional theory calculations and materials properties analysis. It offers diverse tools and modules for structure analysis, property prediction, and error correction, including thermodynamic stability analysis and modeling of chemically disordered materials, with public access through the AFLOW website and search API. | aflow is a computational software package for first-principles calculations and high-throughput materials science. It enables researchers to study materials properties, electronic structure, and phase stability using density functional theory (DFT) calculations. | Some core features of aflow include: 1. High-throughput screening of materials properties, 2. Prediction of phase stability and electronic structure, 3. Automated workflows for DFT calculations, 4. Database integration for materials discovery and design. | https://aflow.org/aflow-school/ | Materials Modeling & Simulation | Condensed Matter Physics | Physics & Physical Sciences | Computational Software, Materials Science, Density Functional Theory | https://aflowlib.org/ | Physical Sciences | https://aflow.org/aflow-school/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.2.11 | Scientific Software | |
afplot | Anvil | Afplot is a tool to plot allele frequencies in VCF files. | The afplot software is a tool designed for plotting allele frequency distributions, which are commonly used in population genetic analyses and genetic diversity studies. It allows users to visualize the distribution of allele frequencies across a population or a set of individuals. | 1. Plotting allele frequency distributions\r 2. Customizable visualization options\r 3. Supports data from population genetic studies\r 4. Easy-to-use interface for generating plots\r 5. Helpful for analyzing genetic diversity and population structure |
Tool | Genetics | Biological Sciences | Allele Frequency, Population Genetics, Genetic Diversity, Data Visualization, Population Structure | https://github.com/sndrtj/afplot | Biological Sciences | https://github.com/sndrtj/afplot#Examples | Anvil: https://www.rcac.purdue.edu/software/afplot | Anvil: 0.2.1 | Data Visualization | ||
afterqc | Anvil | Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data. AfterQC can simply go through all fastq files in a folder and then output three folders: good, bad and QC folders, which contains good reads, bad reads and the QC results of each fastq file/pair. | afterQC is a quality control tool for high-throughput sequencing data. It performs post-alignment quality control on next-generation sequencing data to provide comprehensive QC metrics and visualizations. | Some core features of afterQC include adapter trimming, read filtering, read trimming, quality control metrics generation, and visualization of QC reports. | https://github.com/OpenGene/AfterQC | Application | Sciences | Biology | Quality Control, High-Throughput Sequencing Data, Next-Generation Sequencing | https://github.com/OpenGene/AfterQC | Biological Sciences | https://github.com/OpenGene/AfterQC#Simple-usage | Anvil: https://www.rcac.purdue.edu/software/afterqc | Anvil: 0.9.7 | Bioinformatics | |
agat | Anvil | Agat is a suite of tools to handle gene annotations in any GTF/GFF format | AGAT (Annotation-based Genome Assembly Toolkit) is a pipeline designed for comprehensive annotation and evaluation of genome assemblies. | Genome Assembly Annotation, Evaluation Of Genome Assemblies, Identification Of Genes & Regulatory Elements, Functional Annotation Of Genomic Features | https://agat.readthedocs.io/en/latest/index.html | Pipeline | Genome Annotation | Genomics | Genome Assembly, Annotation, Evaluation, Genomic Analysis | https://github.com/NBISweden/AGAT?tab=readme-ov-file | Biological Sciences | https://agat.readthedocs.io/en/latest/agat_how_does_it_work.html | Anvil: https://www.rcac.purdue.edu/software/agat | Anvil: 0.8.1 | Bioinformatics | |
agfusion | Anvil | AGFusion (pronounced 'A G Fusion') is a python package for annotating gene fusions from the human or mouse genomes. | agfusion is a computational tool for annotating and predicting the effects of gene fusions in cancer. It integrates multiple algorithms to identify and characterize gene fusions using RNA sequencing data. | 1. Detection of gene fusions in cancer genomes\r 2. Annotation and classification of gene fusions\r 3. Prediction of functional consequences of gene fusions\r 4. Integration of multiple algorithms for accurate fusion detection\r 5. Analysis of fusion breakpoints and potential fusion partners |
https://github.com/murphycj/AGFusion | Computational | Cancer Genomics | Bioinformatics | Computational Tool, Gene Fusions, Cancer | https://github.com/murphycj/AGFusion | Biological Sciences | https://github.com/murphycj/AGFusion?tab=readme-ov-file#examples https://www.agfusion.app/ |
Anvil: https://www.rcac.purdue.edu/software/agfusion | Anvil: 1.3.11 | Research Tool | |
ai | Bridges-2 | PyTorch AI development environment | AI, or artificial intelligence, refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning, reasoning, problem-solving, perception, and language understanding. | Core features of AI include machine learning, neural networks, natural language processing, computer vision, and robotics. AI systems can be designed to perform tasks such as speech recognition, decision-making, visual perception, and language translation. | https://www.psc.edu/resources/software/ai/ | Software | Artificial Intelligence, Machine Learning, Neural Networks, Natural Language Processing, Computer Vision, Robotics | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/ai | Bridges-2: Pytorch_23.02-1.13.1-Py3, Tensorflow_23.02-2.10.0-Py3 | Artificial Intelligence & Intelligent Systems | |||||
aiohttp | Aces, Faster | aiohttp is an asynchronous HTTP Client/Server for asyncio and Python. Description Source: https://docs.aiohttp.org/en/stable/ |
aiohttp is an asynchronous HTTP client/server framework for Python. It allows for handling HTTP requests and responses in an asynchronous manner, making it ideal for building high-performance web applications. | Asynchronous Client & Server Components For Http, Websockets Support, Middleware Support For Extending Functionality, Ssl/Tls Support For Secure Communication | https://docs.aiohttp.org/en/stable/ | Http Client/Server Framework | Python Library, Web Development, Asynchronous Programming | https://github.com/aio-libs/aiohttp | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.8.3, 3.8.5 Faster: 3.8.1 |
Web Framework | ||||
alfred | Anvil | Alfred is an efficient and versatile command-line application that computes multi-sample quality control metrics in a read-group aware manner. | Alfred is a productivity application for macOS that boosts your efficiency with hotkeys, keywords, text expansion, and more. It allows users to perform various tasks quickly using customizable keyboard shortcuts. | Customizable Hotkeys For Various Actions, Keyword-Based Search For Files, Contacts, & Web Searches, Text Expansion For Frequently Used Phrases, Clipboard History & Management, Integration With Various Apps & Workflows | https://www.gear-genomics.com/docs/alfred/ | Application | Sciences | Biology | Productivity, Macos, Keyboard Shortcuts, Automation | https://github.com/tobiasrausch/alfred | Other Computer & Information Sciences | https://www.gear-genomics.com/docs/alfred/cli/ | Anvil: https://www.rcac.purdue.edu/software/alfred | Anvil: 0.2.5, 0.2.6 | Productivity Tool | |
alien-hunter | Anvil | Alien-hunter is an application for the prediction of putative Horizontal Gene Transfer (HGT) events with the implementation of Interpolated Variable Order Motifs (IVOMs). | Application | Sciences | Biology | https://www.sanger.ac.uk/tool/alien_hunter/ | Anvil: https://www.rcac.purdue.edu/software/alien-hunter | Anvil: 1.7.7 | Bioinformatics | |||||||
alignstats | Anvil | AlignStats produces various alignment, whole genome coverage, and capture coverage metrics for sequence alignment files in SAM, BAM, and CRAM format. | AlignStats is a software tool for the statistical analysis of biological sequence alignments. It provides various statistical metrics and analyses to investigate the patterns and properties of sequence alignments. | Statistical Analysis Of Biological Sequence Alignments, Calculation Of Sequence Conservation Scores, Identification Of Conserved Regions, Generation Of Graphical Visualizations Of Alignment Statistics | https://github.com/jfarek/alignstats | Statistical Analysis Tool | Genetics | Biological Sciences | Bioinformatics, Sequence Analysis, Alignment, Statistics | https://github.com/jfarek/alignstats | Biological Sciences | https://github.com/jfarek/alignstats?tab=readme-ov-file#usage-examples | Anvil: https://www.rcac.purdue.edu/software/alignstats | Anvil: 0.9.1 | Bioinformatics Tool | |
all-architectures | Ookami | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: All-Architectures | |||||||||||||
allocations | Bridges-2 | PSC Allocations usage utilities | Bridges-2: https://www.psc.edu/resources/software/allocations | Bridges-2: 1.0 | ||||||||||||
allpathslg | Anvil | Allpathslg is a whole-genome shotgun assembler that can generate high-quality genome assemblies using short reads. | Application | Sciences | Biology | https://software.broadinstitute.org/allpaths-lg/blog/ | Anvil: https://www.rcac.purdue.edu/software/allpathslg | Anvil: 52488 | Bioinformatics | |||||||
alphafold | Aces, Anvil, Darwin, Faster | AlphaFold, the state-of-the-art AI system developed by DeepMind, is able to computationally predict protein structures with unprecedented accuracy and speed. Description Source: https://alphafold.ebi.ac.uk/about |
AlphaFold is a deep learning-based system developed by DeepMind to predict protein folding and 3D structure with high accuracy. | AlphaFold uses a novel attention-based neural network architecture that interprets the amino acid sequence of a protein and predicts its 3D structure. It leverages evolutionary information from multiple sequence alignments to improve prediction accuracy. The system also provides confidence scores for its predictions. | https://github.com/google-deepmind/alphafold | Web Application | Structural Biology | Bioinformatics | Protein Folding, Structure Prediction, Deep Learning, Neural Networks | https://alphafold.ebi.ac.uk/ | Biological Sciences | https://github.com/google-deepmind/alphafold?tab=readme-ov-file#installation-and-running-your-first-prediction | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/alphafold Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.3.2-Cuda-11.8.0 Anvil: 2.1.1, 2.2.0, 2.2.3, 2.3.0, 2.3.1 Faster: 2.1.1, 2.2.2-Cuda-11.3.1 |
Prediction Tool | |
alphapickle | Aces, Faster | AlphaPickle is a versatile Python script designed to extract and present output data from DeepMind's ALPHAFOLD protein prediction algorithm, simplifying complex .pkl and .json files into user-friendly formats, alongside generating plots for easier analysis. | Alphapickle is a Python library that provides tools and utilities for working with alpha factors and optimizing portfolio construction in quantitative finance. | Automated alpha factor research, portfolio optimization, backtesting, risk management tools, performance analysis, support for common financial data formats. | https://github.com/mattarnoldbio/alphapickle | Data Analysis | Quantitative Finance | Financial Engineering | Python Library, Quantitative Finance, Alpha Factors, Portfolio Optimization | Other Mathematics | https://github.com/mattarnoldbio/alphapickle | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.4.1 Faster: 1.4.1 |
Library | ||
alsa-lib | Faster | The Advanced Linux Sound Architecture (ALSA) provides audio and MIDI functionality to the Linux operating system. Description Source: https://www.alsa-project.org/wiki/Main_Page |
Advanced Linux Sound Architecture (ALSA) provides audio and MIDI functionality to the Linux operating system. alsa-lib is a library that provides an interface for programmers to access sound card capabilities. | 1. Allows access to sound card capabilities in Linux\r 2. Provides audio and MIDI functionality\r 3. Supports various audio formats\r 4. Offers low latency audio processing\r 5. Enables hardware-level audio control |
https://www.alsa-project.org/wiki/Documentation | Audio Library | Linux, Audio, Library | https://www.alsa-project.org/wiki/Main_Page | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.2.8 | Library | ||||
amask | Stampede3 | The amask tool exposes the process masks (affinity) of an application will have in a parallel environment, so that users can determine the cores/hardware-threads where each process is allowed to run. | Amask is a high-level molecular visualization program that is designed to create and manipulate atomic structures for research and educational purposes. It provides a user-friendly interface for visualizing complex molecular structures and interactions. | 1. Interactive manipulation of molecular structures\r 2. Visualization of atomic interactions and bonds\r 3. Rendering quality images and animations of molecular simulations\r 4. Support for various file formats commonly used in molecular modeling\r 5. User-friendly interface for easy navigation and editing |
https://github.com/TACC/amask | Molecular Visualization Software | Molecular Visualization, Atomic Structures, Molecular Modeling, Research Tool | https://tacc.utexas.edu/research/tacc-research/amask/ | Biological Sciences | https://github.com/TACC/amask/blob/master/README | Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ | Stampede-3: 1.0 | Visualization | |||
amber | Anvil, Expanse, Faster | Amber is a suite of biomolecular simulation programs together with Amber tools. | Amber is a suite of highly extensible molecular simulation programs. It is designed for simulations of biomolecules such as proteins, nucleic acids, and carbohydrates, and can also be used for small molecules. | 1. Molecular dynamics simulations\r 2. Free energy calculations\r 3. Quantum chemistry\r 4. Structural analysis\r 5. Visualization tools |
https://ambermd.org/doc12/Amber23.pdf | Molecular Dynamics | Biophysics, Structural Biology | Biochemistry & Molecular Biology | Molecular Dynamics, Biomolecular Simulations, Quantum Chemistry | https://ambermd.org/ | Biological Sciences | https://ambermd.org/tutorials/ | Anvil: https://www.rcac.purdue.edu/software/amber Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 20 Expanse: C6Gwmih-Omp, Ulauqq7-Omp Faster: 20-Cuda-11.4.1-Nccl-2.11.4-Python-3.9.5, 20-Cuda-11.4.1-Python-3.9.5 |
Simulation | |
ambertools | Aces, Faster | Ambertools is a suite can of complete molecular dynamics simulations, with either explicit water or generalized Born solvent models. | AmberTools is a suite of software for molecular dynamics simulations, energy minimization, and trajectory analysis in the field of computational chemistry. It provides tools for the refinement and analysis of biomolecular structures. | AmberTools offers a wide range of functionality for molecular dynamics simulations, including energy minimization, molecular dynamics simulation, structure analysis, and visualization. It supports various force fields and parameters for simulating biomolecules. | https://ambermd.org/doc12/Amber23.pdf | Simulation Software | Structural Biology | Biophysics | Molecular Dynamics, Computational Chemistry, Biomolecular Structure, Energy Minimization | https://ambermd.org/AmberTools.php | Biological Sciences | https://ambermd.org/tutorials/ | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 22.3 Faster: 21.12 |
Software Tools | |
amd-rocm | Darwin | AMD ROCm is a comprehensive software ecosystem tailored for GPU-accelerated computing tasks, offering robust support for parallel processing and machine learning applications. | https://rocm.docs.amd.com/en/latest/index.html | Toolkit | https://www.amd.com/en/developer/resources/rocm-hub.html | Environment | ||||||||||
amd-uprof | Darwin | AMD uProf (“MICRO-prof”) is a software profiling analysis tool for x86 applications running on Windows, Linux and FreeBSD operating systems and provides event information unique to the AMD “Zen”-based processors and AMD Instinct™ MI Series accelerators. AMD uProf enables the developer to better understand the limiters of application performance and evaluate improvements. | AMD uProf is a performance analysis tool suite for AMD processors that provides detailed insights into application performance and power usage. It allows developers to analyze code performance, identify bottlenecks, and optimize applications for AMD platforms. | 1. Performance analysis tools for AMD processors.\r 2. Detailed insights into application performance.\r 3. Power usage analysis.\r 4. Code optimization capabilities.\r 5. Identify performance bottlenecks. |
https://www.amd.com/content/dam/amd/en/documents/developer/version-4-2-documents/uprof/uprof-user-guide-v4.2.pdf | Compiler/Profiler | Software Engineering, Systems, & Development | Computer Science | Performance Analysis, Application Optimization, Amd Processors | https://www.amd.com/en/developer/uprof.html | Computer & Information Sciences | Performance Analysis Tool | ||||
amdblis | Anvil, Expanse | AMD Optimized BLIS is a portable software framework for instantiating high-performance BLAS-like dense linear algebra libraries. | Amdblis is a computational software for analyzing and visualizing single-molecule data, particularly for biophysical studies. | Amdblis includes tools for data analysis from single-molecule experiments, such as particle tracking, dwell time analysis, and fluorescence analysis. It also offers visualization capabilities for generating plots and heat maps. | https://github.com/flame/blis | Computational Tool | Single-Molecule Biophysics | Biophysics | Computational Software, Data Analysis, Visualization | https://www.amd.com/es/developer/aocl/blis.html | Biological Sciences | https://github.com/flame/blis | Anvil: https://www.rcac.purdue.edu/software/amdblis Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 3.0 Expanse: Zcuungw-Omp, 6Sfatsa |
Data Analysis & Visualization | |
amdfftw | Anvil, Expanse | An AMD optimized version of FFTW. FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST). We believe that FFTW, which is free software, should become the FFT library of choice for most applications. Description Source: https://www.fftw.org/ |
https://github.com/amd/amd-fftw | Library | Engineering | Mathematics | https://www.fftw.org/ | https://www.fftw.org/fftw3_doc/Tutorial.html | Anvil: https://www.rcac.purdue.edu/software/amdfftw Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 3.0 Expanse: T757St4, Zqoqbjf-Omp, ... |
Mathematics | |||||
amdlibflame | Anvil, Expanse | libFLAME AMD Optimized version is a portable library for dense matrix computations, providing much of the functionality present in Linear Algebra Package LAPACK. It includes a compatibility layer, FLAPACK, which includes complete LAPACK implementation. | AMD LIBFLAME is an open-source software library that provides a high-performance implementation of the dense linear algebra routines on CPUs. It aims to offer efficient and robust algebraic computations for numerical linear algebra applications. | High-Performance Implementation Of Dense Linear Algebra Routines On Cpus, Open-Source Nature For Accessibility & Customization, Efficient & Robust Algebraic Computations For Numerical Linear Algebra Applications | https://github.com/amd/libflame | Library | Engineering | Mathematics | Linear Algebra, Numerical Computations, Performance Optimization | https://www.amd.com/en/developer/aocl/blis.html#AOCL-libflame | Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/amdlibflame Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 3.0 Expanse: F37Pl2Z |
Computational Software | ||
amdlibm | Anvil, Expanse | AMD LibM is a software library containing a collection of basic math functions optimized for x86-64 processor-based machines. It provides many routines from the list of standard C99 math functions. Applications can link into AMD LibM library and invoke math functions instead of compilers math functions for better accuracy and performance. | AMDlibm is a software library provided by AMD that offers mathematical functions specifically optimized for high performance on AMD processors. It provides a collection of mathematical functions designed to exploit the advanced features of AMD processors for enhanced numerical computation. | Some core features of amdlibm include optimized mathematical functions for common operations such as elementary functions (e.g., sin, cos), exponential and logarithmic functions, and more. The library is optimized to leverage the advanced capabilities of AMD processors to achieve high performance and accurate computation results. | https://github.com/amd/aocl-libm-ose | Math Library | Engineering | Mathematics | Mathematics, Numerical Computation, Math Library | https://www.amd.com/de/developer/aocl/libm.html | Engineering & Technology | Anvil: https://www.rcac.purdue.edu/software/amdlibm Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 3.0 Expanse: Uil3Tqx |
Library | ||
amdscalapack | Anvil, Expanse | ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines. It depends on external libraries including BLAS and LAPACK for Linear Algebra computations. | https://github.com/amd/aocl-scalapack | Library | Engineering | Mathematics | https://www.amd.com/de/developer/aocl/scalapack.html | Anvil: https://www.rcac.purdue.edu/software/amdscalapack Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 3.0 Expanse: 7Qg2Ts5 |
Mathematics | ||||||
amduprof | Delta, Expanse | AMD uProf (“MICRO-prof”) is a software profiling analysis tool for x86 applications running on Windows, Linux and FreeBSD operating systems and provides event information unique to the AMD “Zen”-based processors and AMD Instinct™ MI Series accelerators. AMD uProf enables the developer to better understand the limiters of application performance and evaluate improvements. | amduprof is a tool developed for profiling OpenCL applications on AMD GPUs. It provides insights into the performance of OpenCL kernels by analyzing memory access patterns, kernel occupancy, and compute unit utilization. | Profiling Opencl Applications, Analyzing Memory Access Patterns, Identifying Kernel Occupancy, Monitoring Compute Unit Utilization | https://www.amd.com/content/dam/amd/en/documents/developer/uprof-v4.0-gaGA-user-guide.pdf | Tool | Artificial Intelligence & Intelligent Systems | Computer Science | Gpu Profiling, Opencl Profiler, Performance Analysis | https://www.amd.com/en/developer/uprof.html | Computer & Information Sciences | https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/debug_perf.html | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Delta: 3.5, 3.6, 4.0 Expanse: 3.4.475 |
Performance Profiler | |
amos | Faster | The AMOS consortium is committed to the development of open-source whole genome assembly software. | AMOS (A Modular Open-Source Assembler) is a collection of tools and techniques for assembly of DNA sequences. It includes a robust collection of assembly algorithms and pipeline components for analyzing data from common next-generation sequencing platforms. | DNA Sequence Assembly, Next-Generation Sequencing Data Analysis, Modular & Open-Source Framework, Various Assembly Algorithms | https://amos.sourceforge.net/wiki/index.php/AMOS#Documentation | Sequence Assembly Software | Genomics | Genetics | Assembly, DNA Sequencing, Bioinformatics | http://amos.sourceforge.net | Biological Sciences | https://amos.sourceforge.net/wiki/index.php/Programmer%27s_guide | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.1.0 | Bioinformatics Tool | |
amphora2 | Faster | An Automated Phylogenomic Inference Pipeline for Bacterial and Archaeal Sequences. | Amphora2 is a bioinformatics tool designed for the accurate and rapid estimation of phylogenetic placement of metagenomic reads. It facilitates the taxonomic classification of microbial sequences within complex environmental samples. | 1. Phylogenetic placement of metagenomic reads\r 2. Taxonomic classification of microbial sequences\r 3. Accurate estimation of phylogenetic relationships\r 4. Rapid analysis of complex environmental samples |
Computational Software | Ecology | Biological Sciences | Bioinformatics, Metagenomics, Phylogenetics | https://github.com/wu-lab-uva/AMPHORA2 | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 20190730-Java-13-Pthreads-Avx2 | Bioinformatics Tool | |||
amptk | Anvil | Amptk is a series of scripts to process NGS amplicon data using USEARCH and VSEARCH, it can also be used to process any NGS amplicon data and includes databases setup for analysis of fungal ITS, fungal LSU, bacterial 16S, and insect COI amplicons. | Amplicon analysis and metabarcoding toolkit (amptk) is a bioinformatics pipeline for analyzing high-throughput amplicon sequencing data such as 16S rRNA gene sequences and Internal Transcribed Spacer (ITS) sequences. It provides various modules for processing raw sequence data, including demultiplexing, quality filtering, denoising, chimera removal, operational taxonomic unit (OTU) picking, taxonomic assignment, and diversity analysis. | 1. Demultiplexing and quality filtering of raw sequencing data.\r 2. Denoising and dereplication of sequences to remove errors.\r 3. Chimera removal to improve the accuracy of data.\r 4. OTU picking based on clustering at specified sequence similarities.\r 5. Taxonomic assignment of OTUs using reference databases.\r 6. Diversity analyses for comparing microbial communities. |
https://amptk.readthedocs.io/en/latest/ | Application | Sciences | Biological Sciences | Bioinformatics, Amplicon Analysis, Metabarcoding, High-Throughput Sequencing, 16S Rrna Gene, Its Sequences | https://github.com/nextgenusfs/amptk | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/amptk | Anvil: 1.5.4 | Bioinformatics | ||
anaconda | Anvil, Darwin, Jetstream, Ookami | Anaconda3 is a popular open-source distribution of Python and R for scientific computing, data science, and machine learning. It simplifies package management and deployment by bundling numerous libraries and tools, and it includes the conda package manager, which makes installing, running, and updating various packages and their dependencies convenient. | Anaconda is a free and open-source distribution of Python and R programming languages for scientific computing, that aims to simplify package management and deployment. | Anaconda includes over 250 popular data science packages and their dependencies such as NumPy, pandas, scipy, scikit-learn, and Jupyter, along with conda package manager for managing virtual environments and deploying packages. | https://docs.anaconda.com/index.html | Package Management | Informatics, Analytics & Information Science | Data Science, Scientific Computing, Package Management, Python, R | https://www.anaconda.com/ | Computer & Information Sciences | https://docs.anaconda.com/free/anaconda/getting-started/ https://www.youtube.com/watch?v=YJC6ldI3hWk https://www.datacamp.com/tutorial/installing-anaconda-mac-os-x https://docs.anaconda.com/ae-notebooks/ |
Anvil: https://www.rcac.purdue.edu/software/anaconda Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Anvil: 2021.05-Py38 Jetstream: 22.9.0 Ookami: 3 |
Software Development | ||
anaconda2 | Bridges-2 | Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda. | Anaconda2 is a free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. It includes over 720 open-source packages and is widely used for data science, machine learning, and scientific computing. | 1. Simplified package management through the conda package manager. 2. Includes a wide range of commonly used scientific computing libraries and tools. 3. Supports Python and R programming languages. 4. Cross-platform compatibility for Windows, macOS, and Linux. 5. Integrated environments such as Jupyter Notebook for interactive computing. | Distribution | Python Libraries, Conda Packages, Data Science, Scientific Computing, Machine Learning, Computational Software | Computer & Information Sciences, Artificial Intelligence & Intelligent Systems | Bridges-2: https://www.psc.edu/resources/software/anaconda2 | Bridges-2: 2019.10 | Scientific Computing | ||||||
anaconda3 | Aces, Bridges-2, Expanse, Faster | Anaconda3 is a popular open-source distribution of Python and R for scientific computing, data science, and machine learning. It simplifies package management and deployment by bundling numerous libraries and tools, and it includes the conda package manager, which makes installing, running, and updating various packages and their dependencies convenient. | Anaconda is a free and open-source distribution of Python programming language for scientific computing that aims to simplify package management and deployment. It includes over 250 popular data science packages and their dependencies, making it a one-stop solution for Python programming in data science, machine learning, deep learning, and other related fields. | Comprehensive Python Distribution For Scientific Computing, Package Management With Conda Package Manager, Includes Popular Data Science Packages Like Numpy, Pandas, Matplotlib, Etc., Cross-Platform Support, Ability To Create Isolated Environments For Different Projects | https://docs.anaconda.com/index.html | Development Tools | Python, Data Science, Machine Learning, Deep Learning, Package Management | https://www.anaconda.com/ | Computer & Information Sciences | https://docs.anaconda.com/free/anaconda/getting-started/ https://www.youtube.com/watch?v=YJC6ldI3hWk https://www.datacamp.com/tutorial/installing-anaconda-mac-os-x https://docs.anaconda.com/ae-notebooks/ |
Aces: https://hprc.tamu.edu/software/aces/ Bridges-2: https://www.psc.edu/resources/software/anaconda3 Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2021.11, 2022.05, 2022.10, 2023.03-1, 2023.07-2, 2024.02-1 Bridges-2: 2020.07, 2020.11, 2022.10 Expanse: Kfluefz, Q4Munrg Faster: 2020.11, 2021.05, 2021.11, 2022.05, 2022.10, 2023.03-1, 2023.07-2, ... |
Programming Language Distribution | |||
anaconda3_cpu | Delta | Anaconda3 is a popular open-source distribution of Python and R for scientific computing, data science, and machine learning. It simplifies package management and deployment by bundling numerous libraries and tools, and it includes the conda package manager, which makes installing, running, and updating various packages and their dependencies convenient. | Anaconda is a popular package and environment manager for Python and R programming languages. Anaconda3 specifically refers to the Python 3 version of Anaconda, which includes a wide range of pre-installed scientific computing packages and libraries. The CPU version indicates that it is optimized for central processing unit (CPU) computations. | 1. Bundled with a wide range of scientific computing packages and libraries\r 2. Supports package management and environment creation\r 3. Includes tools for data science, machine learning, and scientific computing\r 4. Cross-platform compatibility for Windows, macOS, and Linux\r 5. Optimized for CPU-based computations |
https://docs.anaconda.com/index.html | Environment Manager | Data Science, Scientific Computing, Machine Learning | Package Manager, Python Environment, Scientific Computing, Data Science, Machine Learning | https://www.anaconda.com/ | Computer & Information Sciences | https://docs.anaconda.com/free/anaconda/getting-started/ https://www.youtube.com/watch?v=YJC6ldI3hWk https://www.datacamp.com/tutorial/installing-anaconda-mac-os-x https://docs.anaconda.com/ae-notebooks/ |
Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 23.3.1, 23.7.4 | Package Management | ||
anaconda3_gpu | Delta | Anaconda3 is a popular open-source distribution of Python and R for scientific computing, data science, and machine learning. It simplifies package management and deployment by bundling numerous libraries and tools, and it includes the conda package manager, which makes installing, running, and updating various packages and their dependencies convenient. | https://docs.anaconda.com/index.html | Application | https://www.anaconda.com/ | https://docs.anaconda.com/free/anaconda/getting-started/ https://www.youtube.com/watch?v=YJC6ldI3hWk https://www.datacamp.com/tutorial/installing-anaconda-mac-os-x https://docs.anaconda.com/ae-notebooks/ |
Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 22.10.0, 23.3.1, ... | Python And R Repo | |||||||
anaconda3_mi100 | Delta | Anaconda3 is a popular open-source distribution of Python and R for scientific computing, data science, and machine learning. It simplifies package management and deployment by bundling numerous libraries and tools, and it includes the conda package manager, which makes installing, running, and updating various packages and their dependencies convenient. | https://docs.anaconda.com/index.html | Application | https://www.anaconda.com/ | https://docs.anaconda.com/free/anaconda/getting-started/ https://www.youtube.com/watch?v=YJC6ldI3hWk https://www.datacamp.com/tutorial/installing-anaconda-mac-os-x https://docs.anaconda.com/ae-notebooks/ |
Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 4.14.0, 23.7.4 | Python And R Repo | |||||||
anaconda3_rcpu | Delta | Anaconda3 is a popular open-source distribution of Python and R for scientific computing, data science, and machine learning. It simplifies package management and deployment by bundling numerous libraries and tools, and it includes the conda package manager, which makes installing, running, and updating various packages and their dependencies convenient. | https://docs.anaconda.com/index.html | Application | https://www.anaconda.com/ | https://docs.anaconda.com/free/anaconda/getting-started/ https://www.youtube.com/watch?v=YJC6ldI3hWk https://www.datacamp.com/tutorial/installing-anaconda-mac-os-x https://docs.anaconda.com/ae-notebooks/ |
Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 22.9.0 | Python And R Repo | |||||||
anaconda3_x86_64 | Delta | Anaconda is a free, open-source distribution of Python and R programming languages for scientific computing, that aims to simplify package management and deployment. It includes hundreds of popular data science, machine learning, and scientific computing packages. | 1. Simplified package management through conda package manager. 2. Includes popular data science and machine learning libraries like Numpy, Pandas, Scikit-learn, TensorFlow, etc. 3. Enables easy creation of virtual environments for different projects. 4. Jupyter notebook integration for interactive coding and data visualization. 5. Supports Windows, macOS, and Linux platforms. | Distribution | Software Distribution, Scientific Computing, Data Science, Machine Learning | Other Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 23.3.1, 23.7.4 | Package Manager | |||||||
ananse | Anvil | ANANSE is a computational approach to infer enhancer-based gene regulatory networks (GRNs) and to identify key transcription factors between two GRNs. | Ananse is a software tool used for analyzing and visualizing network structures, including complex biological networks. | Ananse offers functionalities for network visualization, analysis, and manipulation. It supports various network types, such as protein-protein interaction networks, gene regulatory networks, and metabolic networks. Users can apply different algorithms for network analysis, clustering, and identifying important network nodes. The tool also provides interactive visualization options for exploring network properties. | https://anansepy.readthedocs.io/en/master/ | Tool | Sciences | Biological Sciences | Network Analysis, Visualization, Biological Networks | https://github.com/vanheeringen-lab/ANANSE | Other Natural Sciences | https://anansepy.readthedocs.io/en/master/examples/ | Anvil: https://www.rcac.purdue.edu/software/ananse | Anvil: 0.4.0 | Data Analysis | |
anchorwave | Anvil | Anchorwave is used for sensitive alignment of genomes with high sequence diversity, extensive structural polymorphism and whole-genome duplication variation. | AnchorWave is a computational software for the analysis and prediction of RNA secondary structures. It uses statistical thermodynamics and dynamic programming algorithms to calculate the minimum free energy structure of RNA sequences. | Prediction Of RNA Secondary Structures, Calculation Of Minimum Free Energy Structures, Utilizes Statistical Thermodynamics, Incorporates Dynamic Programming Algorithms | https://github.com/baoxingsong/AnchorWave | Computational Tool | Biophysics | Bioinformatics | Computational Software, Bioinformatics, RNA Secondary Structures, Thermodynamics, Dynamic Programming | https://github.com/baoxingsong/AnchorWave | Biological Sciences | https://github.com/baoxingsong/AnchorWave?tab=readme-ov-file#example | Anvil: https://www.rcac.purdue.edu/software/anchorwave | Anvil: 1.0.1, 1.1.1 | Prediction Tool | |
angsd | Anvil, Faster | Angsd is a software for analyzing next generation sequencing data. | angsd is a software for analyzing Next Generation Sequencing (NGS) data such as genome-wide association studies (GWAS) and population genomics data. | Some core features of angsd include genotype likelihood estimation, mapping quality control, allele frequency estimation, phylogenetic analysis, and population genetic analysis. | https://www.popgen.dk/angsd/index.php/ANGSD | Application | Sciences | Biology | Ngs Data Analysis, Genome-Wide Association Studies, Population Genomics, Genetic Variation | https://github.com/ANGSD/angsd | Biological Sciences | https://www.popgen.dk/angsd/index.php/Quick_Start | Anvil: https://www.rcac.purdue.edu/software/angsd Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 0.935, 0.937, 0.939, 0.940 Faster: 0.935 |
Bioinformatics | |
annogesic | Anvil | ANNOgesic is the swiss army knife for RNA-Seq based annotation of bacterial/archaeal genomes. | ANNOgesic is a software tool designed to analyze RNA-seq data for the identification of various elements in bacterial genomes. It integrates multiple steps of RNA-seq analysis to predict transcription start sites (TSSs), operon structures, small RNAs, RNA-RNA interactions, and RNA motifs. | Identification Of Transcription Start Sites (Tsss), Prediction Of Operon Structures, Detection Of Small RNAs, Analysis Of RNA-RNA Interactions, Identification Of RNA Motifs | https://annogesic.readthedocs.io/en/latest/index.html | Tool | Genetics | Biological Sciences | RNA-Seq Analysis, Bacterial Genomes, Transcription Start Sites, Operon Structures, Small RNAs, RNA Motifs, RNA-RNA Interactions | https://github.com/Sung-Huan/ANNOgesic | Biological Sciences | https://annogesic.readthedocs.io/en/latest/tutorial.html | Anvil: https://www.rcac.purdue.edu/software/annogesic | Anvil: 1.1.0 | Bioinformatics | |
annovar | Anvil | ANNOVAR is an efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, hg38, as well as mouse, worm, fly, yeast and many others). | ANNOVAR is a powerful software tool designed to annotate genetic variants detected from diverse genomes. | Variant Annotation, Gene-Based Annotations, Functional Prediction, Prioritize Variants, Population Frequencies, Conservation Scores | https://annovar.openbioinformatics.org/en/latest/ | Bioinformatics Tool | Sciences | Biology | Genomics, Genetic Variation, Bioinformatics, Annotation | https://annovar.openbioinformatics.org/en/latest/ | Biological Sciences | https://annovar.openbioinformatics.org/en/latest/user-guide/startup/ | Anvil: https://www.rcac.purdue.edu/software/annovar | Anvil: 2022-01-13 | Genomic Annotation Tool | |
ansys | Bridges-2, Faster | ANSYS is an engineering simulation software used for testing and predicting the behavior of components and systems in various fields. It offers tools for finite element analysis (FEA), computational fluid dynamics (CFD), and other multiphysics simulations, enabling engineers to analyze performance, durability, and fluid dynamics under real-world conditions. | Ansys provides engineering simulation software used to predict how product designs will behave and how manufacturing processes will operate in real-world environments. The software enables engineers to simulate interactions of all disciplines like structural, fluids, heat transfer, electromagnetic, and systems engineering. | Key features of Ansys include structural analysis, computational fluid dynamics (CFD), explicit dynamics, multiphysics, electronics thermal management, and additive manufacturing simulation. | Engineering Simulation Software | Engineering | Mechanical Engineering | Engineering, Simulation, Product Design | https://www.ansys.com/ | Engineering & Technology | Bridges-2: https://www.psc.edu/resources/software/ansys Faster: https://hprc.tamu.edu/software/faster/ |
Bridges-2: 201, 212, 221, 222 Faster: 2022R2 Stampede-3: 24.1 |
Simulation Software | |||
ant | Aces, Expanse, Faster | Apache Ant is a Java library and command-line tool whose mission is to drive processes described in build files as targets and extension points dependent upon each other. The main known usage of Ant is the build of Java applications. Ant supplies a number of built-in tasks allowing to compile, assemble, test and run Java applications. Description Source: https://ant.apache.org/ |
Ant is a build automation tool that is mainly used for Java projects. It automates the process of compiling and building Java applications, along with tasks such as testing and deployment. | Ant provides a simple XML-based build file that outlines the steps needed to build a project. It facilitates the compilation of Java code, running tests, packaging applications, and deploying them. Ant is extensible and can be integrated with other tools and libraries. | https://ant.apache.org/manual/ | Tool | Automation, Java, Build Tool, Deployment | https://ant.apache.org/ | Computer Science | https://www.tutorialspoint.com/ant/ant_quick_guide.htm https://www.vogella.com/tutorials/ApacheAnt/article.html |
Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.10.11-Java-11, 1.10.12-Java-11 Expanse: Hcgc7Fk, 5Soub24 Faster: 1.10.5-Java-1.8, 1.10.9-Java-11, 1.10.11-Java-11, 1.10.12-Java-11 |
Build Automation | |||
antismash | Anvil | Antismash allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genomes. | AntiSMASH is a comprehensive software tool for the automatic genome mining, analysis, and annotation of biosynthetic gene clusters (BGCs) in microbial genomes. It is widely used in bioinformatics and drug discovery research to identify and characterize secondary metabolite biosynthesis pathways. | Detection & Annotation Of Gene Clusters Involved In Secondary Metabolite Production, Prediction Of Putative Functions Of Biosynthetic Enzymes, Identification Of Potential Bioactive Compounds & Natural Products, Visualization Of Gene Clusters & Biosynthetic Pathways, Integration Of Multiple Bioinformatics Tools & Databases | https://docs.antismash.secondarymetabolites.org/ | Annotation Tool | Genomics | Bioinformatics | Bioinformatics, Genome Mining, Biosynthetic Gene Clusters, Secondary Metabolites | https://docs.antismash.secondarymetabolites.org/ | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/antismash | Anvil: 5.1.2, 6.0.1, 6.1.0 | Genomics & Bioinformatics Tools | ||
antlr | Aces, Faster | ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. Description Source: https://www.antlr.org/ |
ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. | Powerful Parser Generator, Support For Multiple Programming Languages, Parsing Expression Grammar (Peg) Support, Automatic Ast Construction, Lexer & Parser Generation | https://www.antlr.org/api/ | Toolkit | Compiler, Parser Generator, Syntax Analysis, Code Generation | https://www.antlr.org/ | https://tomassetti.me/antlr-mega-tutorial/ | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.7.7-Java-11 Faster: 2.7.7-Java-11 |
Compilers | ||||
anvio | Anvil, Bridges-2 | Anvio is an analysis and visualization platform for 'omics data. | Anvi'o is an analysis and visualization platform for omics data. It is designed to help researchers explore complex microbial datasets and perform various tasks such as binning, genome assembly, metagenomic analysis, and visualization. | Some core features of Anvi'o include metagenomic binning, interactive data exploration, genome assembly visualization, multi-omics integration, and phylogenetic profiling. | https://github.com/merenlab/anvio | Bioinformatics Tool | Microbiome Research | Biological Sciences | Omics Data Analysis, Microbiome, Metagenomics, Bioinformatics | https://anvio.org/ | Biological Sciences | https://anvio.org/learn/ | Anvil: https://www.rcac.purdue.edu/software/anvio Bridges-2: https://www.psc.edu/resources/software/anvio |
Anvil: 7.0, 7.1_Main, 7.1_Structure Bridges-2: 7 |
Analysis & Visualization Platform | |
any2fasta | Anvil, Faster | Any2fasta can convert various sequence formats to FASTA. | any2fasta is a tool for converting sequence data in various formats to the standard FASTA format. It allows users to easily convert DNA, RNA, protein sequences, and other biological sequence data into the FASTA format for compatibility with a wide range of bioinformatics tools and databases. | 1. Convert sequence data to FASTA format\r 2. Support for DNA, RNA, protein sequences\r 3. Compatible with a variety of sequence data formats\r 4. Simple and user-friendly interface for quick conversions |
https://github.com/tseemann/any2fasta | Bioinformatics Tool | Genetics | Biological Sciences | Sequence Data, Fasta Format, Bioinformatics | https://github.com/tseemann/any2fasta | Natural Sciences | https://github.com/tseemann/any2fasta?tab=readme-ov-file#examples | Anvil: https://www.rcac.purdue.edu/software/any2fasta Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 0.4.2 Faster: 0.4.2 |
Data Conversion | |
aocc | Aces, Anvil, Bridges-2, Delta, Expanse, Faster, Ookami | AOCC a set of production compilers optimized for software performance when running on AMD host processors using the AMD “Zen” core architecture.The AOCC compiler environment simplifies and accelerates development and tuning for x86 applications built with C, C++, and Fortran languages. Description Source: https://www.amd.com/en/developer/aocc.html |
The AMD Optimizing C/C++ Compiler (AOCC) is a high performance compiler suite with support for C, C++, and Fortran programming languages. | AOCC is designed to provide high performance on AMD processors by leveraging advanced optimizations and features specific to AMD architectures. It offers enhanced vectorization, link-time optimization, and improved code generation. | https://www.amd.com/content/dam/amd/en/documents/developer/version-4-1-documents/aocc/aocc-4.1-user-guide.pdf | Service | Compiler, C, C++, Fortran, Optimization | https://www.amd.com/en/developer/aocc.html | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/aocc Bridges-2: https://www.psc.edu/resources/software/aocc Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 4.0.0 Anvil: 3.1.0 Bridges-2: 2.2.0, 2.3.0 Delta: 4.1.0 Expanse: Io3S466 Faster: 3.1.0 Jetstream: Aocc-Compiler-4.0.0 Ookami: 3.0.0 |
Compiler | ||||
aocc compiler | Jetstream | AOCC a set of production compilers optimized for software performance when running on AMD host processors using the AMD “Zen” core architecture.The AOCC compiler environment simplifies and accelerates development and tuning for x86 applications built with C, C++, and Fortran languages. Description Source: https://www.amd.com/en/developer/aocc.html |
The AMD Optimizing C/C++ Compiler is a high performance compiler suite that builds upon the Open64 compiler infrastructure. It includes support for the latest C and C++ standards, as well as numerous advanced optimization features for AMD processors. | Support For The Latest C & C++ Standards, Advanced Optimization Features For Amd Processors, Built Upon The Open64 Compiler Infrastructure | https://www.amd.com/content/dam/amd/en/documents/developer/version-4-1-documents/aocc/aocc-4.1-user-guide.pdf | Compilers | Compiler, C/C++, Optimization, Amd | https://www.amd.com/en/developer/aocc.html | Computer & Information Sciences | Compiler | ||||||
aocl | Bridges-2, Darwin | AOCL is a set of numerical libraries optimized for AMD processors based on the AMD “Zen” core architecture and generations. The tuned implementations of industry-standard math libraries enable rapid development of scientific and high-performance computing applications. Description Source: https://www.amd.com/en/developer/aocl.html |
The Intel FPGA SDK for OpenCL (aocl) is a software development kit that allows developers to create high-performance FPGA-accelerated applications using OpenCL. It provides a framework for FPGA programming with OpenCL, enabling developers to leverage the parallel processing capabilities of FPGAs for accelerating their applications. | 1. Allows developers to target Intel FPGAs for acceleration.\r 2. Supports OpenCL for FPGA programming.\r 3. Provides optimization tools for FPGA design.\r 4. Enables developers to harness the parallel processing power of FPGAs.\r 5. Facilitates high-performance computing through FPGA acceleration. |
https://www.amd.com/content/dam/amd/en/documents/developer/version-4-1-documents/aocl/aocl-4-1-user-guide.pdf | Compiler | Engineering | Mathematics | Fpga, Opencl, Acceleration | https://www.amd.com/en/developer/aocl.html | Engineering & Technology | Bridges-2: https://www.psc.edu/resources/software/aocl | Bridges-2: 3.1.0 | Development Tools | ||
aocl-sparse | Expanse | AOCL-Sparse contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD processors. In addition, AOCL-Sparse includes iterative sparse solvers for solving linear system of equations. It is designed to be used with C and C++. | The aocl-sparse tool is part of the Intel FPGA SDK for OpenCL and is designed for optimizing sparse matrix operations on FPGAs. It provides a framework for developing custom sparse matrix kernels and integrating them into OpenCL applications for high-performance computing. | Optimizes Sparse Matrix Operations On Fpgas, Supports Custom Sparse Matrix Kernels Development, Integration With Opencl Applications For Hpc, Enhanced Performance For Sparse Matrix Computations | https://github.com/amd/aocl-sparse | Library | Engineering | Mathematics | Sparse Matrix Operations, Fpga Optimization, Opencl Applications, High-Performance Computing | https://www.amd.com/en/developer/aocl/sparse.html | Engineering & Technology | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Fg4Cxoj | Compiler/Tool | ||
apptainer | Jetstream | Apptainer, formerly known as Singularity, is an open-source container platform designed to create portable and reproducible environments for scientific computing. It allows users to package applications, their dependencies, and data in a single container that can be run consistently across different computing environments. Description Source: https://apptainer.org/ |
Apptainer is a tool for creating and managing containerized applications in a simplified and efficient manner. It provides a user-friendly interface for developers and system administrators to package, distribute, and deploy applications using containerization technology. | Creation & Management Of Containerized Applications, User-Friendly Interface, Packaging, Distribution, & Deployment Of Applications, Support For Containerization Technology, Simplified Application Lifecycle Management | https://apptainer.org/documentation/ | Development | Containerization, Application Management, Devops, Software Development | https://apptainer.org/ | Engineering & Technology | https://apptainer.org/docs/user/main/quick_start.html | Jetstream: 1.1.6 | Software Tools | ||||
apr | Aces, Faster | APR (Apache Portable Runtime) is a library that provides a set of APIs designed to abstract away the details of the operating system, thereby offering a consistent interface for programming tasks across different platforms. It facilitates the development of portable applications by providing a standardized set of functions for network communication, file system access, and other system utilities, enhancing portability and reducing the complexity of handling OS-specific differences. | The Apache Portable Runtime (APR) is a software library that provides a predictable and consistent interface to underlying platform-specific implementations. | APR provides a set of APIs that abstract many operating system-specific functionalities, such as file I/O, networking, threading, and inter-process communication. It aims to simplify the development of cross-platform applications by providing a common API for various operating system functions. | https://apr.apache.org/docs/apr/1.7/modules.html | Development | Software Library, Cross-Platform Development, Operating System Abstraction | https://apr.apache.org/ | Engineering & Technology | https://people.apache.org/~rooneg/talks/portable-c-with-apr/apr.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.7.0 Faster: 1.7.0 |
Library | |||
apr-util | Aces, Faster | APR-util is a companion library to the Apache Portable Runtime (APR) that provides a set of additional utilities and interfaces for tasks such as database connectivity, XML parsing, and data structures management. It extends the core functionality of APR, offering developers a broader set of tools for building highly portable and scalable applications across different platforms. | Apache Portable Runtime Utility Library (APR-util) provides a set of utility functions to support the Apache Portable Runtime core functionalities. It is a companion library to APR, extending the basic functionality of APR with additional features. | Database & Sql Support, Ldap (Lightweight Directory Access Protocol) Support, Resource Pooling, Xml Parsing, Uri Parsing, Memory Allocation & Management | https://apr.apache.org/docs/apr-util/1.6/modules.html | Library | Utility Library, Apache Portable Runtime, Support Library, Additional Features | https://apr.apache.org/ | https://www.linuxfromscratch.org/blfs/view/svn/general/apr-util.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.6.1 Faster: 1.6.1 |
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arcade-learning-environment | Faster | The Arcade Learning Environment (ALE) is a simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games. It is built on top of the Atari 2600 emulator Stella and separates the details of emulation from agent design. This video depicts over 50 games currently supported in the ALE. | https://github.com/Farama-Foundation/Arcade-Learning-Environment/blob/master/docs/README.md | Framework | Computer Science | Artificial Intelligence | https://github.com/Farama-Foundation/Arcade-Learning-Environment | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.7.3, 0.8.1 | Developer Support | ||||||
archive-zip | Faster | Provides an interface to ZIP archive files. | archive-zip is a simple, easy-to-use Python library for creating, reading, and extracting ZIP archives. It provides functionality to compress and decompress files and directories using the ZIP format. | Creating Zip Archives, Reading Zip Archives, Extracting Files & Directories, Compression & Decompression Using Zip Format | https://metacpan.org/pod/Archive::Zip | Application | Python Library, Zip Archives, Compression, Decompression | https://metacpan.org/pod/Archive::Zip | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.68 | ||||||
archspec | Aces, Faster | Archspec aims at providing a standard set of human-understandable labels for various aspects of a system architecture like CPU, network fabrics, etc. and APIs to detect, query and compare them. Description Source: https://github.com/archspec/archspec |
Archspec is a framework for detecting the architecture of a system and producing a structured representation of its features for further analysis and optimization. It aims to provide insights into the architectural characteristics of a computing system, helping developers understand and leverage these features for performance optimization and code generation. | Detecting System Architecture, Producing Structured Representation Of System Features, Performance Optimization, Code Generation | https://archspec.readthedocs.io/en/latest/ | Framework | Architecture Detection, System Analysis, Performance Optimization, Code Generation | https://github.com/archspec/archspec | Computer & Information Sciences | https://archspec.readthedocs.io/en/latest/getting_started.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.1.2, 0.1.3, 0.1.4, 0.2.0 Faster: 0.1.0-Python-3.8.2, 0.1.0-Python-3.8.6, 0.1.3 |
Software Development | |||
arcs | Anvil | ARCS is a tool for scaffolding genome sequence assemblies using linked or long read sequencing data. | ARCS (Advanced Research Computing Services) is a software platform developed to provide high-performance computing (HPC) services to researchers in various fields. It aims to enhance computational workflows and facilitate complex simulations and data analysis. | High-Performance Computing Services, Advanced Computational Workflows, Support For Complex Simulations, Data Analysis Capabilities | https://github.com/bcgsc/arcs | Research Software | Sciences | Biology | Hpc, Computational Workflows, Data Analysis | https://github.com/bcgsc/arcs | Engineering & Technology | Anvil: https://www.rcac.purdue.edu/software/arcs | Anvil: 1.2.4 | Tools & Platforms | ||
aria2 | Expanse, Faster | aria2 is a utility for downloading files. The supported protocols are HTTP(S), FTP, SFTP, BitTorrent, and Metalink. aria2 can download a file from multiple sources/protocols and tries to utilize your maximum download bandwidth. Description Source: https://aria2.github.io/manual/en/html/aria2c.html |
aria2 is a lightweight multi-protocol & multi-source command-line download utility. It supports HTTP/HTTPS, FTP, SFTP, BitTorrent and Metalink. | Multi-Protocol & Multi-Source Command-Line Download Utility, Supports Http/Https, Ftp, Sftp, Bittorrent, Metalink, Configurable Download Settings, Batch Downloading, Download Resuming, Parallel Downloads | https://aria2.github.io/manual/en/html/aria2c.html | Download Manager | Download Manager, Command-Line Tool, Multi-Protocol, Multi-Source, File Transfer | https://aria2.github.io/ | Computer & Information Sciences, Other Computer & Information Sciences | https://aria2.github.io/manual/en/html/aria2c.html#example | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Expanse: D7R7Iaa, Q32Jtg2 Faster: 1.35.0 |
Utility | |||
aria2-1.15.1 | Faster | Faster: https://hprc.tamu.edu/software/faster/ | ||||||||||||||
ariba | Anvil | ARIBA is a tool that identifies antibiotic resistance genes by running local assemblies. It can also be used for MLST calling. | Ariba is a cloud-based procurement software solution designed to help businesses manage their entire source-to-pay process more efficiently and effectively. It offers a range of modules for procurement, sourcing, contract management, supplier management, and spend analysis. | Automated Procurement Processes, Supplier Management, Sourcing Capabilities, Contract Management, Spend Analysis Tools | https://github.com/sanger-pathogens/ariba | Cloud-Based Software | Sciences | Biology | Procurement Software, Cloud-Based Solution, Source-To-Pay Process Management | https://sanger-pathogens.github.io/ariba/ | https://github.com/sanger-pathogens/pathogen-informatics-training | Anvil: https://www.rcac.purdue.edu/software/ariba | Anvil: 2.14.6 | Procurement | ||
arm | Ookami | The Arm architecture serves as the foundation for processors, known as Processing Elements (PE). It enables interoperability across diverse Arm devices, facilitating software development and execution. | Arm is a software development suite for building and debugging embedded applications on Arm-based devices. It provides tools for optimizing code for performance, debugging, and profiling applications for a wide range of Arm processors. | Arm compiler, Arm debugger, Arm profiler, Code optimization, Debugging tools, Performance analysis tools | https://developer.arm.com/documentation/ | Compiler/Debugger | Electrical, Electronic, & Information Engineering | Engineering & Technology | Software Development, Embedded Applications, Debugging, Performance Optimization | https://developer.arm.com/ | Engineering & Technology | https://learn.arm.com/?icid=devhub:developer:all-pages:nav-link | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: Forge/22.1.1 | Development Tools | |
arm-forge | Expanse | Arm Forge integrates Arm DDT for parallel debugging, Arm MAP for performance profiling, and Arm Performance Reports for summarizing application performance, supporting various parallel architectures like MPI, CUDA, and OpenMP. | https://developer.arm.com/documentation/101136/22-1-3/Arm-Forge/Introduction-to-Arm-Forge | Toolkit | https://developer.arm.com/ | https://developer.arm.com/documentation/101136/22-1-3/Arm-Forge/Introduction-to-Arm-Forge/Online-resources | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 21.0.1-Linux-X86_64 | ||||||||
arm-gnu-toolchain | Aces | The GNU Toolchain for the Arm Architecture releases produced by Arm (referred to as “Arm GNU Toolchain”) enable partners, developers and the community to use new features from recent Arm Architecture and from open-source projects GCC, Binutils, glibc, Newlib, and GDB. | The ARM GNU Toolchain is a collection of tools/libraries used to create applications for embedded ARM processors. It includes the GNU Compiler Collection (GCC) for compiling C/C++ code, GNU Binutils for creating/executing binary files, and GDB for debugging. | Support For Compiling C/C++ Code For Arm Processors, Assembly Language Support, Highly Optimized Code Generation For Embedded Systems, Debugging Capabilities With Gdb, Open-Source Tools With Strong Community Support | https://developer.arm.com/Tools%20and%20Software/GNU%20Toolchain | Compiler | Compiler, Embedded Systems, Arm Processor, Toolchain | https://developer.arm.com/ | Engineering & Technology | https://developer.arm.com/documentation/ka005946/1-0/?lang=en | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 12.3 | Development Tool | |||
arm-gnu-toolchaint | Aces | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 12.3 | |||||||||||||
armadillo | Aces, Delta, Expanse, Faster | Armadillo is a high quality linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use. It provides high-level syntax and functionality deliberately similar to Matlab. Description Source: https://arma.sourceforge.net/ |
Armadillo is a high-quality linear algebra library for the C++ programming language. It aims to provide efficient and easy-to-use classes for common linear algebra operations, with a particular focus on real and complex matrices and vectors. | 1. Fast matrix operations including decomposition, factorization, and vectorization.\r 2. Seamless integration with C++ programming.\r 3. Various advanced features such as sparse matrices, expression templates, and delayed evaluation.\r 4. Extensive documentation and examples for users' convenience.\r 5. Portable and compatible with various operating systems. |
https://arma.sourceforge.net/docs.html | Linear Algebra Library | Software Engineering, Systems, & Development | Computer Science | Linear Algebra, C++ Library | https://arma.sourceforge.net/ | Computer & Information Sciences | https://arma.sourceforge.net/docs.html#example_prog | Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 11.4.3, 12.6.2 Delta: 12.4.0 Expanse: 9.800.3-Openblas Faster: 10.7.5, 11.4.3, 12.6.2 |
Library | |
arpack | Darwin, Stampede3 | ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. (This library is no longer maintained) Description Source: https://lacsi.rice.edu/software/arpak/default.htm |
ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. It is capable of solving complex, real, symmetric, and nonsymmetric eigenvalue problems across different fields of scientific computing. | 1. Solving large scale eigenvalue problems\r 2. Ability to handle complex, real, symmetric, and nonsymmetric eigenvalue problems\r 3. High performance and efficiency\r 4. Available subroutines for integration into various computational environments |
http://li.mit.edu/Archive/Activities/Archive/CourseWork/Ju_Li/MITCourses/18.335/Doc/ARPACK/Lehoucq97.pdf | Library | Numerical Analysis | Applied Mathematics | Computational Software, Linear Algebra, Eigenvalue Problems | https://github.com/inducer/arpack | Mathematics | https://github.com/inducer/arpack/tree/master/EXAMPLES | Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ | Stampede-3: 3.9.1 | Numerical Library | |
arpack-ng | Aces, Anvil, Expanse, Faster | ARPACK-NG is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. | ARPACK (ARnoldi PACKage) is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. The ARPACK-ng project is a re-implementation of the original ARPACK with the goal of improving its usability, maintainability, and performance across a wide range of modern hardware platforms. | ARPACK-NG provides efficient and scalable algorithms for solving large sparse eigenvalue problems, including those arising from applications in physics, chemistry, engineering, and other fields. It supports iterative methods like Arnoldi iteration for computing a few eigenvalues/vectors of a large sparse matrix, with options for finding either the largest or smallest eigenvalues. | https://github.com/opencollab/arpack-ng/tree/master/DOCUMENTS | Library | Mathematics | Linear-Algebra, Eigenvalue Problems, Sparse Matrices, Iterative Methods, Computational Physics, Computational Chemistry, Fortran | https://github.com/opencollab/arpack-ng | Physical Sciences | https://github.com/opencollab/arpack-ng/tree/master/PARPACK/EXAMPLES | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/arpack-ng Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.8.0, 3.9.0 Anvil: 3.8.0 Expanse: Bbylirn, Ccwydfp, ... Faster: 3.8.0, 3.9.0 |
Mathematics | ||
arrayfire | Expanse | ArrayFire is a high performance software library for parallel computing with an easy-to-use API. Its array based function set makes parallel programming more accessible. | ArrayFire is a high-performance software library for parallel computing with an emphasis on GPU acceleration. It provides a broad range of functionality for accelerated computing, including linear algebra, signal processing, statistics, and image processing. | Gpu Acceleration, Parallel Computing, Linear Algebra Operations, Signal Processing, Image Processing, Statistics | https://arrayfire.org/docs/index.htm#gsc.tab=0 | Library | Engineering | Parallel Computing | Software Library, Parallel Computing, Gpu Acceleration, Linear Algebra, Signal Processing, Image Processing, Statistics | https://arrayfire.org/docs/index.htm#gsc.tab=0 | Computer & Information Sciences | https://arrayfire.org/docs/examples.htm#gsc.tab=0 | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Pl6Gadm | Library | |
arriba | Bridges-2 | Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data. It was developed for the use in a clinical research setting. Description Source: https://github.com/suhrig/arriba |
Arriba is a fast and accurate tool for gene fusion detection in RNA-Seq data. It can identify gene fusions, transcript fusions, and fusion transcript isoforms, providing detailed information on their structure. | 1. Gene fusion detection in RNA-Seq data\r 2. Identification of gene fusions, transcript fusions, and fusion transcript isoforms\r 3. Detailed structural information on detected fusions\r 4. Fast and accurate analysis\r 5. Supports multiple input file formats |
https://arriba.readthedocs.io/en/latest/ | Tool | Transcriptomics | Genomics | Software, Gene Fusion Detection, RNA-Seq, Transcriptome Analysis | https://github.com/suhrig/arriba | Biological Sciences | https://hpc.nih.gov/apps/arriba.html | Bridges-2: https://www.psc.edu/resources/software/arriba | Bridges-2: 2.3.0 | Bioinformatics | |
arrow | Aces, Faster | Apache Arrow (incl. PyArrow Python bindings), a cross-language development platform for in-memory data. | Arrow is a cross-language development platform for in-memory data that specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware like CPUs and GPUs. | Cross-Language Development Platform, Columnar Memory Format, Language-Independent, Efficient Analytic Operations, Support For Modern Hardware Like Cpus & Gpus | https://arrow.apache.org/docs/ | Development Platform | Computer Science | Memory Efficiency | Data Processing, Data Analytics, In-Memory Data, Standardized Format | https://arrow.apache.org/ | Computer & Information Sciences | https://arrow.apache.org/cookbook/cpp/ https://arrow.apache.org/cookbook/java/ https://arrow.apache.org/cookbook/py/ https://arrow.apache.org/cookbook/r/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 8.0.0, 11.0.0 Faster: 0.17.1, 6.0.0, 8.0.0 |
Data Processing | |
arrow-r | Faster | R interface to the Apache Arrow C++ library | Arrow-R is an open-source statistical computing and graphics software program based on the R programming language. It provides advanced statistical analysis, data visualization, and modeling capabilities for researchers and statisticians. | 1. Comprehensive statistical analysis tools\r 2. Advanced data visualization capabilities\r 3. Extensive libraries for statistical modeling\r 4. Integration with R programming language\r 5. Support for custom functions and packages\r 6. Interactive graphics and plots |
https://arrow.apache.org/docs/ | Statistical Software | Statistical Analysis | Statistics & Probability | Statistical Computing, Data Visualization, Statistical Modeling, R Programming | https://arrow.apache.org/ | Mathematics | https://arrow.apache.org/cookbook/cpp/ https://arrow.apache.org/cookbook/java/ https://arrow.apache.org/cookbook/py/ https://arrow.apache.org/cookbook/r/ |
Faster: https://hprc.tamu.edu/software/faster/ | Faster: 6.0.0.2-R-4.1.2, 8.0.0-R-4.2.1 | Data Analysis & Visualization | |
arviz | Faster | ArviZ is a Python package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, data storage, model checking, comparison and diagnostics. | ArviZ is a Python package for exploratory analysis of Bayesian models. It provides a common data structure and functions for visualizing and summarizing outputs from Bayesian inference. | 1. Visualization of posterior distributions, traces, and diagnostics\r 2. Summary statistics for posterior samples\r 3. Probability density plots and pair plots for correlations\r 4. Comparison of multiple models\r 5. Goodness-of-fit checks and convergence diagnostics |
https://python.arviz.org/en/latest/index.html | Python Library | Bayesian Statistics | Statistics & Probability | Python Library, Bayesian Inference, Data Visualization | https://github.com/arviz-devs/arviz | Other Mathematics | https://python.arviz.org/en/latest/examples/index.html | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.11.4 | Data Analysis & Visualization | |
ascatngs | Anvil | AscatNGS contains the Cancer Genome Projects workflow implementation of the ASCAT copy number algorithm for paired end sequencing. | ASCA-based copy number and ploidy profiles for NGS data in R | Generation of allele-specific copy number and ploidy profiles from next-generation sequencing (NGS) data using Allele-Specific Copy number Analysis of Tumors (ASCAT) algorithm in R. | https://github.com/cancerit/ascatNgs | Computational | Genetics | Biological Sciences | Copy Number Analysis, Ploidy Profiles, Ngs Data Analysis | https://github.com/cancerit/ascatNgs | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/ascatngs | Anvil: 4.5.0 | Bioinformatics | ||
asciinema | Bridges-2 | asciinema is a suite of tools for recording, replaying, and sharing terminal sessions. Description Source: https://docs.asciinema.org/ |
asciinema is a free and open-source solution for recording terminal sessions and sharing them on the web. It allows users to record their terminal sessions and playback the recordings directly in a terminal emulator. | Record Terminal Sessions, Share Recordings On The Web, Playback Recordings In A Terminal Emulator, Built-In Asciinema Player For Playback, Free & Open-Source | https://docs.asciinema.org/ | Terminal Recorder | Terminal Recording, Web Sharing, Cli Tool | https://asciinema.org/ | Computer & Information Sciences | https://docs.asciinema.org/getting-started/ | Bridges-2: https://www.psc.edu/resources/software/asciinema | Bridges-2: 2.0.2, 2.1.0 | Development Tool | |||
ase | Aces, Faster | ASE is an Atomic Simulation Environment written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simulations. Description Source: https://wiki.fysik.dtu.dk/ase/index.html |
Atomistic Simulation Environment (ASE) is a set of tools and Python modules for setting up, manipulating, running, visualizing, and analyzing atomistic simulations. | ASE provides interfaces to a wide range of electronic structure codes like VASP, LAMMPS, Quantum ESPRESSO, and more. It offers support for different file formats, offers tools for symmetry operations, molecule visualization, and analysis of simulation results. | https://wiki.fysik.dtu.dk/ase/ase/ase.html | Tool | Sciences | Chemistry | Computational Software, Python Library, Molecular Simulations | https://wiki.fysik.dtu.dk/ase/ | Other Natural Sciences | https://wiki.fysik.dtu.dk/ase/tutorials/tutorials.html#tutorials | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.20.1, 3.22.1 Faster: 3.20.1 |
Simulation & Modeling | |
asgal | Anvil | ASGAL (Alternative Splicing Graph ALigner) is a tool for detecting the alternative splicing events expressed in a RNA-Seq sample with respect to a gene annotation. | asgal is a lightweight tool that aligns sequencing reads against a reference genome, generating BAM files, calling SNPs, and creating variant call format (VCF) files. It is designed for usability and simplicity in analyzing large genomic datasets. | Read Alignment Against Reference Genome, Bam File Generation, Snp Calling, Vcf File Creation | https://asgal.algolab.eu/documentation | Alignment & Variant Calling | Sciences | Biology | Genomics, Bioinformatics, Sequence Analysis | https://asgal.algolab.eu/ | Biological Sciences | https://asgal.algolab.eu/documentation#example | Anvil: https://www.rcac.purdue.edu/software/asgal | Anvil: 1.1.7 | Bioinformatics Tools | |
aspera-connect | Anvil, Bridges-2 | IBM Aspera Connect is an install-on-demand application that facilitates high-speed uploads and downloads with an Aspera transfer server. Description Source: https://www.ibm.com/docs/en/aspera-connect/4.1?topic=aspera-connect-user-guide-linux |
https://www.ibm.com/docs/en/aspera-connect/4.1?topic=aspera-connect-user-guide-linux | Application | https://www.ibm.com/aspera/connect/ | https://www.ibm.com/docs/en/aspera-connect/4.2?topic=linux-setting-up-connect | Anvil: https://www.rcac.purdue.edu/software/aspera-connect Bridges-2: https://www.psc.edu/resources/software/aspera-connect |
Anvil: 4.2.6 Bridges-2: 3.11.0.5 |
Data Transfer Tool | |||||||
assembly-stats | Anvil | Assembly-stats is a tool to get assembly statistics from FASTA and FASTQ files. | assembly-stats is a tool for summary statistics of genome assembly, providing information on contig and scaffold lengths, NG(x) statistics, and basic completeness metrics. | - Calculates basic statistics on genome assemblies\r - Provides information on contig and scaffold lengths\r - Calculates NG(x) statistics\r - Evaluates basic completeness metrics |
https://github.com/sanger-pathogens/assembly-stats | Stand-Alone Tool | Sciences | Biology | Genome Assembly, Bioinformatics | https://github.com/sanger-pathogens/assembly-stats | Biological Sciences | https://github.com/sanger-pathogens/assembly-stats?tab=readme-ov-file#example | Anvil: https://www.rcac.purdue.edu/software/assembly-stats | Anvil: 1.0.1 | Bioinformatics Tool | |
assimp | Aces | Open Asset Import Library is a library to load various 3d file formats into a shared, in-memory imediate format. It supports more than 40 file formats for import and a growing selection of file formats for export. Description Source: https://assimp.org/ |
Open Asset Import Library (short name: Assimp) is a portable Open Source library to import various well-known 3D model formats in a uniform manner. The most recent version also knows how to export 3D files and is therefore called Assimp. The library provides a C++ interface. There are also bindings for various other languages available. Assimp aims to provide a full asset conversion pipeline for use in game engines or real-time rendering systems | 1. Import support for multiple 3D model formats. 2. Export support for 3D files. 3. Offers a C++ interface. 4. Provides a full asset conversion pipeline. 5. Portable and Open Source. | https://assimp-docs.readthedocs.io/en/latest/ | 3D Modeling/Rendering | Computer Science | File Loading | 3D Models, Asset Import, Game Development | https://assimp.org/ | Computer & Information Sciences | https://github.com/assimp/assimp/blob/master/Build.md | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 5.2.5 | Library | |
astropy | Faster | Astropy enhances usability and collaboration among astronomy Python packages. | Astropy is a community-driven Python library for astronomy and astrophysics. It aims to provide core functionality and common tools needed for astronomical research. Astropy includes modules for celestial coordinate systems, spectral manipulations, units and constants, time and dates, FITS file handling, and cosmological calculations. | Provides Tools For Astronomical Research In Python, Supports Celestial Coordinate Transformations & Manipulations, Handles Spectral Data & Analysis, Includes Functionality For Time & Date Calculations, Offers Tools For Fits File Handling & Manipulation, Provides Support For Cosmological Calculations | https://docs.astropy.org/en/stable/ | Computational Software | Astrophysics | Astronomy & Planetary Sciences | Python Library, Astronomy, Astrophysics, Astronomical Research, Data Analysis | https://www.astropy.org/ | Physical Sciences | https://learn.astropy.org/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 4.3.1 | Library | |
at-spi2-atk | Aces, Faster | Applications that provide accessibility through the ATK interfaces need a way to translate those interfaces to AT-SPI2 DBus calls. This module, at-spi2-atk, provides that translation bridge. Description Source: https://gitlab.gnome.org/Archive/at-spi2-atk |
at-spi2-atk is the Assistive Technology Service Provider Interface (AT-SPI) for the ATK toolkit, which allows assistive technologies to interact with graphical user interfaces. | Provides an interface for assistive technologies to access and interact with the ATK accessibility library, supports the creation and manipulation of accessible components in graphical user interfaces, enables assistive technologies to receive and respond to events from ATK objects. | https://gitlab.gnome.org/Archive/at-spi2-atk | Interface | General | General | Assistive Technology, Accessibility, User Interface | https://gitlab.gnome.org/Archive/at-spi2-atk | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.38.0 Faster: 2.34.1, 2.38.0 |
Library | ||
at-spi2-core | Aces, Faster | AT-SPI2-Core is the central component of the Assistive Technology Service Provider Interface, providing APIs for assistive technologies to interact with Linux desktop applications, thereby enhancing accessibility for users with disabilities. | AT-SPI (Assistive Technology Service Provider Interface) is a protocol that allows assistive technologies to interact with and control applications. | 1. Provides accessibility support for people with disabilities.\r 2. Allows assistive technologies to query and interact with GUI applications.\r 3. Enables developers to make their applications accessible to assistive technologies. |
https://gnome.pages.gitlab.gnome.org/at-spi2-core/libatspi/ | Library | General | General | Accessibility, Assistive Technology, Gui Applications | https://gitlab.gnome.org/GNOME/at-spi2-core/ | Computer Science | https://wiki.gnome.org/Accessibility/ATK/BestPractices | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.40.3, 2.44.1, 2.46.0, 2.49.91 Faster: 2.34.0, 2.38.0, 2.40.3, 2.44.1, 2.46.0, 2.49.91 |
Accessibility Software | |
atac-seq-pipeline | Anvil | The ENCODE ATAC-seq pipeline is used for quality control and statistical signal processing of short-read sequencing data, producing alignments and measures of enrichment. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/atac-seq-pipeline/atac-seq-pipeline.html |
https://github.com/ENCODE-DCC/atac-seq-pipeline | Application | Sciences | Biology | https://www.encodeproject.org/atac-seq/ | Anvil: https://www.rcac.purdue.edu/software/atac-seq-pipeline | Anvil: 2.1.3 | Bioinformatics | ||||||
ataqv | Anvil | Ataqv is a toolkit for measuring and comparing ATAC-seq results. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/ataqv/ataqv.html |
ataqv is a software tool designed for comparing ATAC-seq and DNase-seq data to identify signal quality metrics and differential accessibility profiles. | ataqv provides quality control metrics, differential accessibility analysis, peak calling, and signal enrichment analysis for ATAC-seq and DNase-seq data. | https://parkerlab.github.io/ataqv/ | Tool | Genomics, Epigenetics | Bioinformatics | Quality Control, Differential Accessibility Analysis, Peak Calling, Signal Enrichment Analysis | https://github.com/ParkerLab/ataqv | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/ataqv | Anvil: 1.3.0 | Computational Biology | ||
atk | Aces, Faster | ATK provides the set of accessibility interfaces that are implemented by other toolkits and applications. Using the ATK interfaces, accessibility tools have full access to view and control running applications. Description Source: https://hprc.tamu.edu/software/aces/ |
The Amsterdam Modeling Suite (AMS) offers a comprehensive set of programs for computational chemistry. One of the key components is the Atomistix ToolKit (ATK) for quantum mechanical and classical atomistic simulations of materials. | ATK enables simulations based on density functional theory (DFT) for electronic structure calculations, molecular dynamics (MD) simulations for atomistic modeling, and a combination of both in quantum mechanics/molecular mechanics (QM/MM) approaches. It supports a wide range of materials properties and advanced analysis tools. | https://docs.gtk.org/atk/ | Simulation Software | Condensed Matter Physics | Physical Sciences | Computational Chemistry, Materials Science, Quantum Mechanics, Molecular Dynamics | https://gitlab.gnome.org/Archive/atk | Physical Sciences | https://wiki.gnome.org/Accessibility/ATK/BestPractices | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.36.0, 2.38.0 Faster: 2.34.1, 2.36.0, 2.38.0 |
Computational Software | |
atlas | Darwin | A library for Numerical Weather Prediction and Climate Modelling | Atlas is a powerful software for managing and visualizing genomic sequencing data. It allows users to analyze large datasets, perform variant calling, and visualize results in an interactive and user-friendly interface. | 1. Genomic data management\r 2. Variant calling\r 3. Visualization tools\r 4. Interactive interface\r 5. Large dataset analysis |
https://sites.ecmwf.int/docs/atlas/c++/ | Analysis Tool | Genomics | Biological Sciences | Genomics, Sequencing, Data Analysis, Visualization | https://github.com/ecmwf/atlas | Biological Sciences | https://confluence.ecmwf.int/display/ATLAS/User+guide?preview=/66984475/66984474/Atlas-user-guide-0.8.0.pdf | Genomic Data Analysis | |||
atop | Delta | Atop is an ASCII full-screen performance monitor for Linux that is capable of reporting the activity of all processes, daily logging of system and process activity for long-term analysis, highlighting overloaded system resources by using colors, etc. Description Source: https://www.atoptool.nl/ |
Atop is an advanced interactive system monitor that includes a variety of functionalities for monitoring and analyzing system performance. It provides a real-time overview of system performance, resource utilization, and process activity. | Real-Time System Monitoring, Resource Utilization Tracking, Dynamic & Interactive Display, Process-Level Monitoring, Detailed System Statistics, Ability To Log Data For Future Analysis | https://github.com/Atoptool/atop | System Monitoring Tool | General | General | System Monitor, Performance Analysis, Resource Utilization, Process Activity, System Statistics | https://www.atoptool.nl/ | Computer & Information Sciences | https://www.atoptool.nl/perftrain.php | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 2.5.0 | Monitoring | |
atp | Delta | Abnormal Termination Processing (ATP) is a tool that monitors Cray system user applications. If an application encounters a fatal signal, ATP will handle the signal and perform analysis on the dying application. Description Source: https://cpe.ext.hpe.com/docs/debugging-tools/atp.1.html |
ATP (Adenosine triphosphate) is a molecule that carries energy within cells. It is considered the energy currency of life and is involved in various cellular processes. | 1. Energy carrier in cells\r 2. Involved in cellular processes like metabolism, muscle contraction, and cell signaling\r 3. Provides energy for biochemical reactions |
https://hpctools.readthedocs.io/en/latest/debug_atp.html | Analytical Tool | Cell Biology | Biochemistry & Molecular Biology | Biology, Biochemistry, Cellular Processes | https://cpe.ext.hpe.com/docs/debugging-tools/atp.1.html | Biological Sciences | https://cpe.ext.hpe.com/docs/debugging-tools/atp.1.html#example-run | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 3.15.1 | Biological Molecule | |
atram | Anvil | aTRAM (automated target restricted assembly method) is an iterative assembler that performs reference-guided local de novo assemblies using a variety of available methods. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/atram/atram.html |
atram is a software package that is developed to automate the assembly of targeted genomic regions from whole-genome shotgun data. It is specifically designed for capturing and assembling large genomic regions, such as mitochondria, chloroplasts, and other organelles. | Automated Assembly Of Targeted Genomic Regions, Designed For Capturing & Assembling Large Genomic Regions, Works With Whole-Genome Shotgun Data, Specifically Tailored For Organelle Assemblies | https://github.com/juliema/aTRAM/blob/master/doc/introduction.md | Genomic Assembly | Genetics | Cell Biology | Genomics, Bioinformatics, Assembly | https://github.com/juliema/aTRAM | Biological Sciences | https://github.com/juliema/aTRAM/blob/master/doc/introduction.md | Anvil: https://www.rcac.purdue.edu/software/atram | Anvil: 2.4.3 | Bioinformatics | |
atropos | Anvil | Atropos is a tool for specific, sensitive, and speedy trimming of NGS reads. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/atropos/atropos.html |
Atropos is a software tool designed for read trimming and adapter detection in Next Generation Sequencing (NGS) data. It aims to accurately identify and remove adapter sequences, poly-A tails, and other types of unwanted sequences from NGS reads. | 1. Adapter detection and trimming\r 2. Quality filtering and read trimming\r 3. Support for multiple sequencing platforms\r 4. Parallel processing for improved efficiency |
https://atropos.readthedocs.io/en/1.1/ | Trimming Tool | Genomics | Bioinformatics | Ngs, Read Trimming, Adapter Detection | https://github.com/jdidion/atropos | Biological Sciences | https://atropos.readthedocs.io/en/1.1/guide.html | Anvil: https://www.rcac.purdue.edu/software/atropos | Anvil: 1.1.17, 1.1.31 | Ngs Analysis | |
attrdict3 | Aces, Faster | AttrDict is an MIT-licensed library that provides mapping objects that allow their elements to be accessed both as keys and as attributes. Description Source: https://github.com/pirofti/AttrDict3 |
attrdict3 is a Python library that provides a dictionary-like object that allows accessing keys like attributes, providing a more convenient way to work with nested dictionaries. | Attribute Access To Dictionary Keys, Nested Dictionary Support, Easy To Use & Intuitive | https://pypi.org/project/attrdict3/ | Library | Sciences | Computer Science | Python Library, Dictionary Wrapper | https://github.com/pirofti/AttrDict3 | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.0.2 Faster: 2.0.2 |
Python Library | ||
augur | Anvil | Augur is the bioinformatics toolkit we use to track evolution from sequence and serological data. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/augur/augur.html |
Augur is a bioinformatics tool designed for phylogenetic analysis of viral genomes. It provides a pipeline for analyzing viral sequence data, performing phylogenetic inference, and visualizing the results. | Phylogenetic Analysis Of Viral Genomes, Pipeline For Viral Sequence Data Analysis, Phylogenetic Inference, Visualization Of Results | https://docs.nextstrain.org/projects/augur/en/stable/ | Sequence Analysis Tool | Phylogenetics | Bioinformatics | Bioinformatics, Phylogenetics, Viral Genomes, Sequence Analysis | https://github.com/nextstrain/augur | Biological Sciences | https://docs.nextstrain.org/projects/augur/en/stable/examples/examples.html | Anvil: https://www.rcac.purdue.edu/software/augur | Anvil: 14.0.0, 15.0.0 | Bioinformatics Tool | |
augustus | Anvil, Bridges-2 | AUGUSTUS is a program that predicts genes in eukaryotic genomic sequences. It can be run on this web server, on a new web server for larger input files or be downloaded and run locally. Description Source: https://bioinf.uni-greifswald.de/augustus/ |
Augustus is a gene prediction software for eukaryotes that uses a probabilistic model to predict genes on genomic sequences. It is widely used in bioinformatics to identify coding regions in DNA sequences. | 1. Gene prediction using probabilistic model\r 2. Prediction of coding regions in eukaryotic genomes\r 3. Incorporation of RNA-Seq data for improved gene prediction accuracy |
https://github.com/Gaius-Augustus/Augustus/tree/master | Bioinformatics Tool | Genomics | Bioinformatics | Gene Prediction, Eukaryotes, Bioinformatics | https://bioinf.uni-greifswald.de/augustus/ | Biological Sciences | https://vcru.wisc.edu/simonlab/bioinformatics/programs/augustus/docs/tutorial2015/training.html | Anvil: https://www.rcac.purdue.edu/software/augustus Bridges-2: https://www.psc.edu/resources/software/augustus |
Anvil: 3.4.0, 3.5.0 Bridges-2: 3.4.0 |
Gene Prediction | |
autoconf | Aces, Darwin, Faster, Kyric | Autoconf is an extensible package of M4 macros that produce shell scripts to automatically configure software source code packages. These scripts can adapt the packages to many kinds of UNIX-like systems without manual user intervention. Autoconf creates a configuration script for a package from a template file that lists the operating system features that the package can use, in the form of M4 macro calls. Description Source: https://www.gnu.org/software/autoconf/ |
Autoconf is a tool for producing configure scripts for building, installing, and packaging software on Unix-like systems. It assists in the process of automating the configuration of software packages and generating portable makefiles. | 1. Generates configure scripts for software packages.\r 2. Helps in checking system features, setting up variables, and creating makefiles.\r 3. Enables the creation of software that can be compiled on different Unix-like systems.\r 4. Facilitates the customization and configuration of software build processes.\r 5. Aids in reducing the complexity of software builds across multiple platforms. |
https://www.gnu.org/software/autoconf/manual/ | Build Tools | General | General | Build Automation, Software Configuration, Makefiles | https://www.gnu.org/software/autoconf/ | Engineering & Technology | https://www.lrde.epita.fr/~adl/autotools.html,https://www.sourceware.org/autobook/ | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.69, 2.71 Faster: 2.69, 2.71 |
Software Development | |
autoconf-archive | Kyric | The GNU Autoconf Archive is a collection of more than 500 macros for GNU Autoconf that have been contributed as free software by friendly supporters of the cause from all over the Internet. Every single one of those macros can be re-used without imposing any restrictions whatsoever on the licensing of the generated configure script. Description Source: https://github.com/autoconf-archive/autoconf-archive |
https://www.gnu.org/software/autoconf-archive/ | Service | General | General | https://github.com/autoconf-archive/autoconf-archive | Utilities | ||||||||
autodock | Anvil | AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. Description Source: https://autodock.scripps.edu/ |
AutoDock is a suite of automated docking tools designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. | Docking Of Small Molecules To Protein Receptors, Prediction Of Binding Modes & Binding Affinities, Analysis Of Molecular Interactions, Virtual Screening For Drug Discovery | https://autodock.scripps.edu/documentation/documentation/ | Bioinformatics Tool | Drug Discovery | Biology | Computational Chemistry, Molecular Docking, Virtual Screening | https://autodock.scripps.edu/ | Biological Sciences | https://ccsb.scripps.edu/projects/docking/ | Anvil: https://www.rcac.purdue.edu/software/autodock | Anvil: 2020.06 | Molecular Docking | |
autodock-gpu | Faster | AutoDock-GPU is an accelerated version of AutoDock4 that is hundreds of times faster than the original single-CPU docking code. Description Source: https://autodock.scripps.edu/ |
AutoDock-GPU is a molecular modeling tool that allows for molecular docking simulations to predict the binding modes of small molecules with biomacromolecules. It utilizes GPU acceleration to significantly speed up the docking process. | 1. Molecular docking simulations for predicting binding modes. \r 2. Utilizes GPU acceleration for faster processing. \r 3. Allows for virtual screening of large compound libraries. \r 4. Effective tool for studying protein-ligand interactions. \r 5. Generates detailed reports on docking results. |
https://github.com/ccsb-scripps/AutoDock-GPU | Simulation Software | Structural Biology | Bioinformatics | Molecular Modeling, Molecular Docking, Biomolecular Interactions, Gpu Acceleration | https://autodock.scripps.edu/ | Biological Sciences | https://ccsb.scripps.edu/projects/docking/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.5.3-Cuda-11.3.1 | Research Tool | |
autodock-vina | Faster | AutoDock Vina is an open-source program for doing molecular docking. AutoDock Vina is one of the docking engines of the AutoDock Suite. | https://vina.scripps.edu/manual/ | Application | Sciences | Biology | https://vina.scripps.edu/ | https://vina.scripps.edu/tutorial/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.1.2-Linux_X86 | Docking, Structural Biology | |||||
automake | Aces, Faster, Kyric | GNU Automake is a tool for automatically generating Makefile.in files compliant with the GNU Coding Standards. Automake requires the use of GNU Autoconf. Description Source: https://www.gnu.org/software/automake/automake.html |
Automake is a build automation tool that automatically generates makefiles for software compilation. | Automates the generation of Makefiles for software projects, simplifies the process of building software, supports the GNU build system, assists in maintaining project consistency and portability. | https://www.gnu.org/software/automake/manual/automake.html | Compiler | General | General | Build Automation, Software Development, Compilers | https://www.gnu.org/software/automake/automake.html | Engineering & Technology | https://www.lrde.epita.fr/~adl/autotools.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.16.2, 1.16.3, 1.16.4, 1.16.5 Faster: 1.16.1, 1.16.2, 1.16.3, 1.16.4, 1.16.5 |
Build Tools | |
autotools | Aces, Faster, Kyric, Stampede3 | Autotools refers to a suite of tools including Autoconf, Automake, and Libtool used in software development for ensuring portability and simplifying the build process. Autoconf is for creating configure scripts, Automake for generating Makefiles, and Libtool for handling shared libraries. | Autotools is a suite of programming tools designed to assist in making source code packages portable across different Unix-like systems. It includes autoconf, automake, libtool, and others and is commonly used in open-source software projects. | 1. Configuration scripts generation for software builds\r 2. Dependency tracking and handling\r 3. Portable Makefiles generation\r 4. Simplified cross-platform compilation\r 5. Integration with various programming languages and build systems |
Build Automation | Software Development | Software Engineering, Systems, & Development | Programming, Software Development, Build Automation | https://autotools.info | Computer & Information Sciences | https://autotools.info/examples.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 20200321, 20210128, 20210726, 20220317 Faster: 20180311, 20200321, 20210128, 20210726, 20220317 Kyric: Autotools Stampede-3: 1.4 |
Development Tools | ||
aws-cli | Anvil, Delta | The AWS Command Line Interface (AWS CLI) is a unified tool to manage your AWS services. Description Source: https://aws.amazon.com/cli/ |
The AWS Command Line Interface (CLI) is a unified tool to manage AWS services from the command line. With just one tool to download and configure, you can control multiple AWS services from the command line and automate them through scripts. | 1. Unified tool to manage various AWS services from the command line.\r 2. Provides commands for a wide range of AWS services including EC2, S3, Lambda, etc.\r 3. Supports scripting and automation of AWS tasks.\r 4. Easy installation and configuration. |
https://docs.aws.amazon.com/cli/ | Command Line Tool | General | General | Aws, Command Line Interface, Cloud Management | https://aws.amazon.com/cli/ | Computer & Information Sciences, Engineering & Technology | https://aws.amazon.com/training/ | Anvil: https://www.rcac.purdue.edu/software/aws-cli Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html |
Anvil: 2.4.15 Delta: 2.13.14 |
Devops & Cloud Tools | |
awscli | Faster | The AWS Command Line Interface (AWS CLI) is a unified tool to manage your AWS services. Description Source: https://aws.amazon.com/cli/ |
The AWS Command Line Interface (CLI) is a unified tool that provides a consistent interface for interacting with various Amazon Web Services (AWS) through the command line. It allows users to manage AWS services and resources directly from the terminal. | Interact With Various Aws Services, Control Multiple Aws Resources, Automate Aws Tasks, Access & Manage Aws Cli Configuration | https://docs.aws.amazon.com/cli/ | Development Tool | General | General | Cloud Computing, Command Line Interface, Aws Services | https://aws.amazon.com/cli/ | Computer & Information Sciences | https://aws.amazon.com/training/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.11.21 | Command Line Interface Tool | |
axl | Faster | AXL is a cross-platform C/C++ support library tailored for large projects, addressing specialized needs like compiler/parser writing and asynchronous IO. | The Application Exchange Library (Axl) is a software framework that provides a comprehensive suite of tools for collaborating with ASE (Atomic Simulation Environment) in Python. Axl facilitates the exchange of python objects for interacting with different computational materials science software packages. | 1. Enable seamless collaboration with ASE in Python. 2. Provides tools for exchanging Python objects. 3. Facilitates interaction with various computational materials science software packages in a unified framework. | https://github.com/vovkos/axl?tab=readme-ov-file | Framework | Atomic Simulation Environment | Other Natural Sciences | Computational Software, Python Library, Materials Science, Software Collaboration | https://github.com/vovkos/axl?tab=readme-ov-file | Physical Sciences | https://vovkos.github.io/axl/build-guide/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 20220413 | Scientific Computing | |
bactopia | Anvil | Bactopia is a flexible pipeline for complete analysis of bacterial genomes. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bactopia/bactopia.html |
Bactopia is a bioinformatics pipeline that leverages best practices and state-of-the-art tools to perform bacterial genome analysis. It automates the process of quality control, assembly, annotation, and more, providing researchers with a streamlined workflow for analyzing bacterial genomes. | Quality Control Of Sequencing Data, Genome Assembly, Functional Annotation, Comparative Genomics, Identification Of Antibiotic Resistance Genes, Phylogenetic Analysis | https://bactopia.github.io/latest/ | Pipeline | Genetics | Biological Sciences | Bioinformatics, Genomics, Bacterial Genome Analysis, Pipeline | https://github.com/bactopia/bactopia | Biological Sciences | https://bactopia.github.io/latest/tutorial/ | Anvil: https://www.rcac.purdue.edu/software/bactopia | Anvil: 2.0.3, 2.1.1, 2.2.0, 3.0.0 | Bioinformatics Tool | |
bali-phy | Anvil, Faster | Bali-phy is a tool for bayesian co-estimation of phylogenies and multiple alignments via MCMC. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bali-phy/bali-phy.html |
bali-phy is a software package for Bayesian inference of phylogenies, evolutionary rates, and divergence times. It is particularly designed for large-scale comparative genomic studies. | Some core features of bali-phy include Bayesian inference of phylogenetic trees, estimation of evolutionary rates and divergence times, handling large-scale datasets efficiently, and conducting rigorous statistical analyses. | https://bali-phy.org/ | Bioinformatics Tool | Phylogenetics, Comparative Genomics | Bioinformatics | Bayesian Inference, Phylogenetics, Evolutionary Biology, Genomics | https://github.com/bredelings/BAli-Phy | Biological Sciences | https://bali-phy.org/Tutorial4.html | Anvil: https://www.rcac.purdue.edu/software/bali-phy Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 3.6.0 Faster: 3.6.0, 3.6.1 |
Computational Biology | |
bam-readcount | Anvil | Bam-readcount is a utility that runs on a BAM or CRAM file and generates low-level information about sequencing data at specific nucleotide positions. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bam-readcount/bam-readcount.html |
bam-readcount is a program that summarizes reference-aligned reads from a BAM file. It is useful for generating read counts at specific genomic positions, such as for variant calling or assessing coverage. | Summarizes Bam File Reads At Specific Genomic Positions, Useful For Variant Calling & Coverage Assessment, Flexible Output Formats For Downstream Analysis | https://github.com/genome/bam-readcount | Command Line Tool | Bioinformatics | Genomics | Bioinformatics, Genomics, Variant-Calling, Coverage-Assessment | https://github.com/genome/bam-readcount | Biological Sciences | https://github.com/genome/bam-readcount/tree/master/tutorial | Anvil: https://www.rcac.purdue.edu/software/bam-readcount | Anvil: 1.0.0 | Bioinformatics Tool | |
bamgineer | Anvil | Bamgineer is a tool that can be used to introduce user-defined haplotype-phased allele-specific copy number variations (CNV) into an existing Binary Alignment Mapping (BAM) file with demonstrated applicability to simulate somatic cancer CNVs in phased whole-genome sequencing datsets. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bamgineer/bamgineer.html |
Bamgineer is a software tool designed for generating and modifying C/C++ source code using a genetic programming approach. It utilizes genetic programming to evolve programs to match a given target set of functionality. | 1. Genetic programming for code generation and modification. 2. Evolves programs to match specified functionality. 3. Supports C/C++ programming languages. | https://github.com/pughlab/bamgineer | Development Tool | Software Engineering, Systems, & Development | Computer Science | Genetic Programming, Code Generation, C/C++ | https://github.com/pughlab/bamgineer | Computer & Information Sciences | https://github.com/pughlab/bamgineer/blob/master/docs/input_preparation.md | Anvil: https://www.rcac.purdue.edu/software/bamgineer | Anvil: 1.1 | Code Generation | |
bamkit | Faster | Tools for common BAM file manipulations. Description Source: https://github.com/hall-lab/bamkit |
BamKit is a toolkit for analyzing and manipulating BAM files, which are binary sequence alignment/map format files commonly used in bioinformatics for storing mapped sequence data. | BamKit provides functionalities for parsing BAM files, extracting alignment statistics, filtering reads, marking duplicates, sorting reads, and indexing BAM files. | Tool | Sciences | Biology | Bioinformatics, Hpc Tools | https://github.com/hall-lab/bamkit | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2017.04.12 | Computational Biology | |||
bamliquidator | Anvil | Bamliquidator is a set of tools for analyzing the density of short DNA sequence read alignments in the BAM file format. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bamliquidator/bamliquidator.html |
bamliquidator is a tool for finding biologically-relevant peak sets in high-throughput sequencing data, particularly ChIP-seq and ATAC-seq data. It helps in identifying enriched regions (peaks) by calculating the fold enrichment compared to control data. | 1. Identifying enriched regions (peaks) in ChIP-seq and ATAC-seq data\r 2. Calculating fold enrichment compared to control data\r 3. Generating statistics and visualization of peak sets\r 4. Providing options for customization and integration with downstream analysis tools |
https://github.com/BradnerLab/pipeline/wiki/bamliquidator | Data Analysis Tool | Chip-Seq & Atac-Seq Data Analysis | Genetics | Bioinformatics, Hpc Tools | https://github.com/BradnerLab/pipeline/wiki/bamliquidator | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/bamliquidator | Anvil: 1.5.2 | Bioinformatics Tool | ||
bamsurgeon | Anvil | Bamsurgeon are tools for adding mutations to .bam files, used for testing mutation callers. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bamsurgeon/bamsurgeon.html |
bamsurgeon is a toolkit for adding mutations to a .bam file for use in testing variant calling pipelines. It can be used to spike in synthetic SNVs, indels, and/or denovo SVs to specific genomic coordinates. | 1. Spike in synthetic single nucleotide variants (SNVs)\r 2. Introduce insertions and deletions (indels) at specified genomic locations\r 3. Add de novo structural variants (SVs) to a given genomic position\r 4. Allow for customization of mutation rate, allele frequency, and mutation type\r 5. Test variant calling pipelines by simulating mutations in a controlled manner |
https://github.com/adamewing/bamsurgeon/blob/master/doc/Manual.pdf | Mutation Simulation | Sciences | Biology | Genomic Data, Mutation Simulation, Variant Calling, Bioinformatics | https://github.com/adamewing/bamsurgeon | Biological Sciences | https://github.com/adamewing/bamsurgeon | Anvil: https://www.rcac.purdue.edu/software/bamsurgeon | Anvil: 1.2 | Bioinformatics Tool | |
bamtools | Aces, Anvil, Bridges-2, Expanse, Faster | BamTools is a project that provides both a C++ API and a command-line toolkit for reading, writing, and manipulating BAM (genome alignment) files. Description Source: https://github.com/pezmaster31/bamtools/wiki |
BamTools is a software toolkit for manipulating BAM (Binary Alignment Map) files. It provides both a C++ API for BAM file input and output, and a command-line tool for performing various operations on BAM files. | Efficient Bam File Reading & Writing, Tools For Filtering, Sorting, Merging, Indexing Bam Files, Support For Extracting Regions, Statistics, & Alignments From Bam Files, Integration With Other Bioinformatics Tools | https://github.com/pezmaster31/bamtools/wiki | Toolkit | Sciences | Biology | Bioinformatics, Bam Files, Sequence Alignment, Toolkit | https://github.com/pezmaster31/bamtools | Biological Sciences | https://genome.sph.umich.edu/wiki/BamUtil:_convert | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/bamtools Bridges-2: https://www.psc.edu/resources/software/bamtools Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.5.2 Anvil: 2.5.1, 2.5.2 Bridges-2: 2.5.1 Expanse: 2.5.1 Faster: 2.5.2 |
Analysis & Manipulation Tools | |
bamutil | Anvil | Bamutil is a collection of programs for working on SAM/BAM files. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bamutil/bamutil.html |
BamUtil is a versatile utility that provides a range of operations for manipulating BAM files, which are binary versions of the Sequence Alignment/Map (SAM) format used in bioinformatics for storing mapped sequencing data. It offers a variety of functions for sorting, merging, indexing, and filtering BAM files efficiently. | Sorting Bam Files, Merging Bam Files, Indexing Bam Files, Filtering Bam Files | https://genome.sph.umich.edu/wiki/BamUtil | Utility | Genomics | Bioinformatics | Bam Files, Sequence Alignment/Map Format, Bioinformatics, Data Manipulation | https://github.com/statgen/bamUtil | Biological Sciences | https://genome.sph.umich.edu/wiki/Category:BamUtil | Anvil: https://www.rcac.purdue.edu/software/bamutil | Anvil: 1.0.15 | Data Manipulation | |
banner | Delta | The banner program is used to print large letters of a given text. If the text is not given on the command line, it will be read from stdin. Description Source: https://linuxcommandlibrary.com/man/banner |
Banner is a comprehensive administrative software solution designed for higher education institutions to manage student information, academic records, financial aid, human resources, and other key administrative functions. | Banner offers modules for student registration, course management, academic advising, billing and payments, financial aid processing, human resources management, reporting and analytics, and more. It provides integration with various systems to streamline administrative processes. | https://www.ibm.com/docs/en/aix/7.3?topic=b-banner-command#banner__title__5 | Commercial | General | General | Administrative Software, Higher Education, Student Information System, Academic Records, Financial Aid Management, Human Resources Management | https://linuxcommandlibrary.com/man/banner | Social Sciences | https://www.ibm.com/docs/en/aix/7.3?topic=b-banner-command#banner__title__5 | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 1.3.5 | Administrative Software | |
barrnap | Anvil | Barrnap: Basic Rapid Ribosomal RNA Predictor. Barrnap predicts the location of ribosomal RNA genes in genomes. Description Source: https://github.com/tseemann/barrnap |
Barrnap is a software tool for rapid ribosomal RNA prediction. It identifies rRNA sequences in DNA sequence data using a profile hidden Markov model (HMM) that is more tuned to ribosomal RNA genes. | 1. Identify ribosomal RNA sequences in DNA data.\r 2. Utilizes a profile hidden Markov model (HMM) for accurate prediction.\r 3. Rapid and efficient rRNA prediction.\r 4. Helps in annotating rRNA genes in genomic data. |
https://github.com/tseemann/barrnap?tab=readme-ov-file#options | Sequence Analysis Tool | Sequence Analysis | Genomics | Bioinformatics, Genomics, Sequence Analysis, Ribosomal RNA, DNA Sequencing | https://github.com/tseemann/barrnap | Biological Sciences | https://github.com/tseemann/barrnap?tab=readme-ov-file#usage | Anvil: https://www.rcac.purdue.edu/software/barrnap | Anvil: 0.9.4 | Bioinformatics Tool | |
basenji | Anvil | Basenji is a tool for sequential regulatory activity predictions with deep convolutional neural networks. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/basenji/basenji.html |
Basenji is a deep learning framework for regulatory genomics that leverages convolutional neural networks (CNNs) to predict transcriptional regulation by learning the patterns of chromatin accessibility, histone modification, and transcription factor binding. | Utilizes Convolutional Neural Networks (Cnns) For Regulatory Genomics, Predicts Transcriptional Regulation By Learning Patterns Of Chromatin Accessibility, Histone Modification, & Transcription Factor Binding, Performs Genome Sequence Segmentation & Regulatory Element Prediction | https://github.com/calico/basenji | Genomics Tool | Regulatory Genomics | Genomics | Deep Learning, Regulatory Genomics, Transcriptional Regulation | https://github.com/calico/basenji | Biological Sciences | https://github.com/calico/basenji?tab=readme-ov-file#tutorials | Anvil: https://www.rcac.purdue.edu/software/basenji | Anvil: 0.5.1 | Deep Learning Framework | |
bat | Bridges-2 | bat tries to achieve the following goals: Provide beautiful, advanced syntax highlighting, integrate with Git to show file modifications, be a drop-in replacement for (POSIX) cat, offer a user-friendly command-line interface. Description Source: https://github.com/sharkdp/bat?tab=readme-ov-file#project-goals-and-alternatives |
BAT (Bioinformatics Analysis Tool) is a bioinformatics software suite designed for the analysis of biological sequence data. | - Sequence Alignment, - Phylogenetic Analysis, - Motif Discovery, - Sequence Annotation | https://github.com/sharkdp/bat | Analysis Tool | Bioinformatics | Genetics | Bioinformatics, Computational Biology | https://github.com/sharkdp/bat | Biological Sciences | https://github.com/sharkdp/bat?tab=readme-ov-file#how-to-use | Bridges-2: https://www.psc.edu/resources/software/bat | Bridges-2: 0.23.0 | Bioinformatics Tool | |
bayescan | Anvil | BayeScan aims at identifying candidate loci under natural selection from genetic data, using differences in allele frequencies between populations. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bayescan/bayescan.html |
BayeScan is a tool used for detecting natural selection from genetic data. It is based on Bayesian model comparisons that enable the identification of loci that are under selection compared to neutral loci. BayeScan uses FST values to differentiate between selected and neutral loci. | 1. Detection of loci under selection from genetic data\r 2. Bayesian model comparisons\r 3. Differentiation between selected and neutral loci using FST values |
https://cmpg.unibe.ch/software/BayeScan/files/BayeScan2.1_manual.pdf | Analysis Tool | Population Genetics | Genetics | Genetic Analysis, Natural Selection, Bayesian Model Comparison | https://cmpg.unibe.ch/software/BayeScan/ | Biological Sciences | https://evomics.org/wp-content/uploads/2016/01/BayeScan_BayeScEnv_exercises.pdf | Anvil: https://www.rcac.purdue.edu/software/bayescan | Anvil: 2.1 | Bioinformatics | |
bazam | Anvil | Bazam is a tool to extract paired reads in FASTQ format from coordinate sorted BAM files. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bazam/bazam.html |
Bazam is a computational software tool developed for analyzing and visualizing structural genetic variants from sequencing data. It provides researchers with a comprehensive set of functionalities to analyze and interpret genomics data. | Structural Genetic Variant Analysis, Sequencing Data Interpretation, Data Visualization Tools | https://github.com/ssadedin/bazam | Bioinformatics Tool | Genomics | Genetics | Computational Software, Bioinformatics, Genomics | https://github.com/ssadedin/bazam | Biological Sciences | https://github.com/ssadedin/bazam?tab=readme-ov-file#simple-example https://github.com/ssadedin/bazam?tab=readme-ov-file#advanced-example |
Anvil: https://www.rcac.purdue.edu/software/bazam | Anvil: 1.0.1 | Data Analysis | |
bazel | Aces, Bridges-2, Faster | Bazel is an open-source build and test tool similar to Make, Maven, and Gradle. It uses a human-readable, high-level build language. Bazel supports projects in multiple languages and builds outputs for multiple platforms. Bazel supports large codebases across multiple repositories, and large numbers of users. Description Source: https://bazel.build/about/intro |
Bazel is a build tool that helps to build and test software of any size, quickly and reliably. | Bazel provides advanced caching and parallel execution for faster builds, support for multiple languages, robust dependency analysis, and scalable resource management. | https://bazel.build/docs | Build & Testing Tools | General | General | Build Tool, Software Testing, Dependency Management, Resource Management | https://bazel.build/ | Engineering & Technology | https://bazel.build/docs#tutorials https://bazel.build/start/cpp |
Aces: https://hprc.tamu.edu/software/aces/ Bridges-2: https://www.psc.edu/resources/software/bazel Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.7.2, 4.2.2, 5.1.1, 6.3.1 Bridges-2: 3.7.1 Faster: 0.26.1, 0.29.1, 2.0.0, 3.6.0, 3.7.2, 4.2.2, 5.1.1, 6.3.1 |
Development Tools & Techniques | |
bbmap | Aces, Anvil, Bridges-2, Faster | Bbmap is a short read aligner, as well as various other bioinformatic tools. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bbmap/bbmap.html |
BBMap is a fast and accurate short-read aligner for mapping DNA sequences to a reference genome. It also includes various bioinformatics tools for sequence alignment, mapping, assembly, and analysis. | 1. High-speed short read aligner. 2. Capable of mapping DNA sequences to a reference genome. 3. Includes various bioinformatics tools for sequence analysis and assembly. 4. Supports various file formats. | https://jgi.doe.gov/data-and-tools/software-tools/bbtools/bb-tools-user-guide/bbmap-guide/ | Bioinformatics Tool | Sequence Analysis | Genomics | Bioinformatics, DNA Sequencing, Sequence Alignment | https://sourceforge.net/projects/bbmap/ | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/bbmap Bridges-2: https://www.psc.edu/resources/software/bbmap Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 38.90 Anvil: 38.93, 38.96 Bridges-2: 39.01 Faster: 38.90, 38.96 |
Sequence Alignment Tool | ||
bbtools | Anvil | BBTools is a suite of fast, multithreaded bioinformatics tools designed for analysis of DNA and RNA sequence data. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bbtools/bbtools.html |
BBTools is a suite of bioinformatics tools designed for use with high-throughput DNA sequencing data. It includes various programs for read trimming, error correction, reference mapping, metagenomics analysis, and more. | Some core features of BBTools include read trimming to remove adapters and low-quality bases, error correction to improve read accuracy, reference mapping for aligning reads to a reference genome, metagenomics analysis for taxonomic classification of sequences, and various utility programs for filtering and manipulating sequencing data. | https://jgi.doe.gov/data-and-tools/software-tools/bbtools/bb-tools-user-guide/ | Tool | Sciences | Biology | Bioinformatics, Sequencing, High-Throughput, DNA, Metagenomics | https://jgi.doe.gov/data-and-tools/software-tools/bbtools/ | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/bbtools | Anvil: 39.00 | Bioinformatics | ||
bcftools | Anvil, Bridges-2, Expanse, Faster | BCFtools is a program for variant calling and manipulating files in the Variant Call Format (VCF) and its binary counterpart BCF. Description Source: https://samtools.github.io/bcftools/howtos/index.html |
bcftools is a set of utilities that manipulate variant calls in the Variant Call Format (VCF) and its binary counterpart (BCF). It provides functionality for filtering, viewing, converting, and annotating variant data. | Some core features of bcftools include variant calling, filtering and comparison of VCF/BCF files, genotype calling, statistical tests for association studies, subsetting and merging VCF files, and generating consensus sequences. | https://samtools.github.io/bcftools/bcftools.html | Bioinformatics Tool | Bioinformatics | Genomics | Variant Calling, Genomics, Bioinformatics | https://github.com/samtools/bcftools | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/bcftools Bridges-2: https://www.psc.edu/resources/software/bcftools Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 1.13, 1.14, 1.17 Bridges-2: 1.10.2 Expanse: 5Zeidhh Faster: 1.14 |
Computational Software | ||
bcl2fastq | Anvil | BCL2FASTQ is a software tool that converts raw sequencing data from Illumina sequencing instruments into the FASTQ format, enabling bioinformatic analysis of genomic sequences. | bcl2fastq is a software tool developed by Illumina that converts base call files (BCL) generated by Illumina sequencers into FASTQ files, which are commonly used for downstream sequence data analysis. | Some core features of bcl2fastq include demultiplexing of sequencing data, barcode processing, quality score calculation, adapter trimming, and outputting high-quality FASTQ files ready for further analysis. | https://support.illumina.com/content/dam/illumina-support/documents/documentation/software_documentation/bcl2fastq/bcl2fastq2-v2-20-software-guide-15051736-03.pdf | Sequence Data Processing | Sciences | Biology | Sequencing Data, Fastq Files, Illumina Sequencers | https://support.illumina.com/sequencing/sequencing_software/bcl2fastq-conversion-software.html | Biological Sciences | https://www.youtube.com/watch?v=gz3H_pcLe7c | Anvil: https://www.rcac.purdue.edu/software/bcl2fastq | Anvil: 2.20.0 | Bioinformatics | |
beagle | Anvil | Beagle is is a software package for phasing genotypes and for imputing ungenotyped markers. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/beagle/beagle.html |
Beagle is a high-performance software library for phylogenetic inference using maximum likelihood methods. It can be used for reconstructing large phylogenetic trees from molecular sequence data with high efficiency and accuracy. | Beagle offers support for a wide range of DNA and protein substitution models, parallel processing on multiple CPU cores, and SIMD vectorization to accelerate likelihood calculations. It also includes functionalities for handling large datasets efficiently. | https://faculty.washington.edu/browning/beagle/beagle_5.4_18Mar22.pdf | Library | Phylogenetics | Genetics | Phylogenetic Inference, Maximum Likelihood, Molecular Sequence Data, Parallel Processing, Likelihood Calculations | https://faculty.washington.edu/browning/beagle/beagle.html | Biological Sciences | https://faculty.washington.edu/browning/beagle/run.beagle.01Mar24.d36.example | Anvil: https://www.rcac.purdue.edu/software/beagle | Anvil: 5.1_24Aug19.3E8, 5.1 | Computational Biology | |
beagle-lib | Faster | BEAGLE is a high-performance library that can perform the core calculations at the heart of most Bayesian and Maximum Likelihood phylogenetics packages. It can make use of highly-parallel processors such as those in graphics cards (GPUs) found in many PCs. Description Source: https://github.com/beagle-dev/beagle-lib |
Beagle-lib is a high-performance library for evaluating the likelihood of sequence evolution on phylogenetic trees. It is designed to implement the BEAGLE (Broad-platform Evolutionary Analysis General Likelihood Evaluator) application programming interface (API) for helping in tasks related to phylogenetic inference in computational biology. | 1. High-performance likelihood calculations for phylogenetic inference. 2. Implementing the BEAGLE API for efficient computation on both CPU and GPU architectures. 3. Provides functionalities for assessing sequence evolution on large phylogenetic trees. 4. Supports parallel processing for faster calculations. 5. Optimized for handling complex evolutionary models and large datasets efficiently. | https://github.com/beagle-dev/beagle-lib?tab=readme-ov-file#documentation | Library | Sciences | Biology | Computational Biology, Phylogenetic Inference, Likelihood Evaluation, Evolutionary Analysis, Bioinformatics | https://github.com/beagle-dev/beagle-lib | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.1.2, 4.0.0 | Bioinformatics | |||
beast | Faster | BEAST 2 is a cross-platform program for Bayesian phylogenetic analysis of molecular sequences. Description Source: https://www.beast2.org/ |
BEAST is a cross-platform program for Bayesian analysis of molecular sequences using MCMC (Markov Chain Monte Carlo) methods. It is widely used for phylogenetic inference, divergence time estimation, and molecular dating. | 1. Bayesian phylogenetic inference\r 2. Divergence time estimation\r 3. Molecular dating\r 4. Cross-platform compatibility\r 5. MCMC methods for parameter estimation |
https://www.beast2.org/xml/index.html | Tool | Evolutionary Biology | Systems Biology | Bioinformatics, Computational Biology, Phylogenetics, Molecular Evolution, Bayesian Analysis | https://www.beast2.org/ | Biological Sciences | https://www.beast2.org/tutorials/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.6.7, 2.7.3 | Statistical Analysis | |
beast1 | Expanse | BEAST is a cross-platform program for Bayesian analysis of molecular sequences using MCMC. Description Source: https://beast.community/ |
https://beast.community/ | Application | Sciences | Biology | https://github.com/beast-dev/beast-mcmc | https://beast.community/getting_started | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: A4Ztrbb, Uuirrt3 | Bioinformatics | |||||
beast2 | Anvil, Expanse | BEAST 2 is a cross-platform program for Bayesian phylogenetic analysis of molecular sequences. Description Source: https://www.beast2.org/ |
BEAST2 is a cross-platform program for Bayesian evolutionary analysis of molecular sequences. It is widely used for estimating species trees, gene trees, divergence times, substitution rates, and demographic parameters using various models of sequence evolution. | 1. Bayesian inference for molecular sequences analysis\r 2. Estimation of species trees, gene trees, divergence times, substitution rates, and demographic parameters\r 3. Wide range of substitution models and clock models\r 4. Incorporation of fossil constraints and birth-death models\r 5. Advanced Markov chain Monte Carlo (MCMC) algorithms\r 6. Integration with other tools like BEAGLE library for high-performance computing |
https://www.beast2.org/xml/index.html | Tool | Phylogenetics | Ecology | Phylogenetics, Evolutionary Analysis, Molecular Sequences, Bayesian Inference | https://www.beast2.org/ | Biological Sciences | https://www.beast2.org/tutorials/ | Anvil: https://www.rcac.purdue.edu/software/beast2 Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 2.6.3, 2.6.4, 2.6.6 Expanse: Bhuvd2X, Ymaff6C |
Bioinformatics | |
beautifulsoup | Aces, Faster | Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. Description Source: https://www.crummy.com/software/BeautifulSoup/bs4/doc/ |
https://www.crummy.com/software/BeautifulSoup/bs4/doc/ | Library | Computer Science | General | https://www.crummy.com/software/BeautifulSoup/ | https://www.datacamp.com/tutorial/web-scraping-using-python https://www.tutorialspoint.com/beautiful_soup/beautiful_soup_quick_guide.htm |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.10.0, 4.11.1, 4.12.2 Faster: 4.10.0 |
Python Library For Parsing | |||||
bedops | Anvil, Bridges-2 | BEDOPS is an open-source command-line toolkit that performs highly efficient and scalable Boolean and other set operations, statistical calculations, archiving, conversion and other management of genomic data of arbitrary scale. Description Source: https://bedops.readthedocs.io/en/latest/ |
BEDOPS is a suite of tools for flexible and highly efficient genomic data analysis. It provides a wide range of operations for working with genomic data, such as set operations, comparisons, and statistical calculations. | Set Operations On Genomic Intervals, Comparisons & Statistical Analyses, Highly Efficient & Flexible Data Analysis Tools, Support For Various Genomic Data Formats, Command-Line Interface | https://bedops.readthedocs.io/en/latest/content/reference.html | Command-Line Tool | Genomics | Bioinformatics | Genomic Data Analysis, Bioinformatics, Computational Biology, Genomics, Data Analysis | https://bedops.readthedocs.io/en/latest/ | Biological Sciences | https://bedops.readthedocs.io/en/latest/content/usage-examples.html | Anvil: https://www.rcac.purdue.edu/software/bedops Bridges-2: https://www.psc.edu/resources/software/bedops |
Anvil: 2.4.39 Bridges-2: 2.4.39 |
Genomic Data Analysis Tool | |
bedtools | Aces, Anvil, Bridges-2, Faster | Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. This is an older version of bedtools2. Description Source: https://bedtools.readthedocs.io/en/latest/ |
Bedtools is a software suite for the comparison, manipulation, and annotation of genomic features in multiple formats. | Bedtools enables users to intersect, merge, count, complement, and shuffle genomic intervals from multiple files. It facilitates the identification of overlaps between different genomic features, such as peaks, gene annotations, and other genomic regions. | https://bedtools.readthedocs.io/en/latest/ | Application | Sciences | Biology | Bioinformatics, Genomics, Data Analysis, Tool | https://github.com/arq5x/bedtools | Biological Sciences | https://bedtools.readthedocs.io/en/latest/content/example-usage.html https://sandbox.bio/tutorials/bedtools-intro |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/bedtools Bridges-2: https://www.psc.edu/resources/software/bedtools Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.31.0 Anvil: 2.30.0, 2.31.0 Bridges-2: 2.29.2, 2.30.0 Faster: 2.30.0 |
Bioinformatics | |
bedtools2 | Expanse | Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. Description Source: https://bedtools.readthedocs.io/en/latest/ |
Bedtools2 is a powerful suite of tools for manipulating genomic features and annotations. It allows users to perform a wide range of tasks on genomic intervals, such as intersecting, merging, comparing, and analyzing BED, GFF, VCF, and other common genomic file formats. | 1. Intersecting genomic intervals\r 2. Merging overlapping features\r 3. Comparing genomic files\r 4. Filtering and manipulating genomic data\r 5. Calculating coverage and overlaps\r 6. Handling multiple file formats |
https://bedtools.readthedocs.io/en/latest/content/bedtools-suite.html | Tool | Sciences | Biology | Genomic Data Analysis, Bed Files, Bioinformatics | https://github.com/arq5x/bedtools2 | Biological Sciences | https://bedtools.readthedocs.io/en/latest/content/example-usage.html https://sandbox.bio/tutorials/bedtools-intro |
Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 5Anbfkq | Genomic Analysis | |
berkeley-db | Expanse, Kyric | Berkeley DB is a family of embedded key-value database libraries providing scalable high-performance data management services to applications. Description Source: https://docs.oracle.com/database/bdb181/ |
https://libdb.org/docs/db/5.3.21/ | Library | Computer Science | Storage, Hpc Applications | https://www.oracle.com/database/technologies/related/berkeleydb.html | https://docs.oracle.com/database/bdb181/ https://www.oracle.com/database/technologies/berkeleydb-db-faq.html |
Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 18.1.40 | Developer Support | |||||
berkeley-upc | Faster | Unified Parallel C (UPC) is an extension of the C programming language designed for high performance computing on large-scale parallel machines.The language provides a uniform programming model for both shared and distributed memory hardware. Description Source: https://upc.lbl.gov/ |
https://upc.lbl.gov/docs/ | Programming Language | Computer Science | Hpc Applications, Parallel Computing | https://upc.lbl.gov/ | https://upc.lbl.gov/demos/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2022.10.0 | Developer Support | |||||
binutils | Aces, Darwin, Faster | The GNU Binutils are a collection of binary tools. The main ones are: ld (the GNU linker), as (the GNU assembler), and gold (a new, faster, ELF only linker). Description Source: https://www.gnu.org/software/binutils/ |
Binutils is a collection of binary tools, including linker (ld), assembler (as), archiver (ar), and other tools to manipulate object files and executables. | Binutils provides essential tools for creating, modifying, and analyzing executable and object files. It includes utilities for linking object files into executables, assembling source code into object files, creating archives, and more. Binutils supports a wide range of binary formats and architectures. | https://sourceware.org/binutils/docs-2.42/ | System Software | General | General | Binary Tools, Linker, Assembler, Object Files | https://www.gnu.org/software/binutils/ | Computer & Information Sciences | https://sourceware.org/binutils/docs-2.34/ld/Options.html#Options | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.32, 2.35, 2.36.1, 2.37, 2.38, 2.39, 2.40 Faster: 2.28, 2.30, 2.31.1, 2.32, 2.34, 2.35, 2.36.1, 2.37, 2.38, 2.39, ... |
Development Tools | |
bio-db-hts | Faster | Perl interface to HTS library for DNA sequencing. Description Source: https://metacpan.org/author/AVULLO |
Bio-db-hts is a Python library that provides an easy-to-use interface for working with HTS (High Throughput Sequencing) data. It allows users to access, manipulate, and analyze biological sequence data obtained from high-throughput sequencing technologies. | Access & Retrieve Hts Data, Manipulate & Analyze Biological Sequence Data, Support For Various Types Of High-Throughput Sequencing Technologies, Integrates With Other Bioinformatics Tools & Libraries | https://metacpan.org/dist/Bio-DB-HTS | Data Analysis | Genomics | Bioinformatics | Python Library, High Throughput Sequencing, Biological Sequence Data, Bioinformatics | https://github.com/Ensembl/Bio-DB-HTS | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.01 | Library | ||
bioawk | Anvil, Faster | Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats, including optionally gzip'ed BED, GFF, SAM, VCF, FASTA/Q and TAB-delimited formats with column names. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bioawk/bioawk.html |
Bioawk is an extension of the AWK programming language, with added functionality specifically designed for processing bioinformatics data. It is an efficient tool for manipulating and analyzing biological data in various formats. | 1. Process and extract information from common bioinformatics file formats such as SAM, BAM, VCF, FASTQ, and GFF.\r 2. Perform complex data manipulation tasks using custom scripts and commands.\r 3. Integrate seamlessly with existing bioinformatics pipelines and tools.\r 4. Handle large-scale datasets efficiently and effectively. |
https://github.com/lh3/bioawk | Scripting Tool | Computational Biology | Bioinformatics | Bioinformatics, Data Processing, File Formats, Data Analysis | https://github.com/lh3/bioawk | Biological Sciences | https://github.com/lh3/bioawk?tab=readme-ov-file#examples | Anvil: https://www.rcac.purdue.edu/software/bioawk Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 1.0 Faster: 1.0 |
Bioinformatics Tool | |
biobambam | Anvil | Biobambam is a collection of tools for early stage alignment file processing. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/biobambam/biobambam.html |
Biobambam is a set of tools for processing BAM files, with a focus on high-throughput sequencing data. It provides efficient and multi-threaded algorithms for tasks such as sorting, merging, indexing, and filtering BAM files. | 1. Efficient processing of BAM files\r 2. Multi-threaded algorithms for improved performance\r 3. Sorting, merging, indexing, and filtering BAM files\r 4. Focus on high-throughput sequencing data\r 5. Compatibility with SAMtools and BAMtools |
https://gitlab.com/german.tischler/biobambam2 | Bioinformatics Tools | Genomics | Genetics | Bioinformatics, Data Processing, High-Throughput Sequencing | https://gitlab.com/german.tischler/biobambam2 | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/biobambam | Anvil: 2.0.183 | Tools | ||
biocontainers | Anvil, Stampede3 | BioContainers is a community-driven project that provides the infrastructure and basic guidelines to create, manage and distribute bioinformatics packages (e.g conda) and containers (e.g docker, singularity). Description Source: https://biocontainers-edu.readthedocs.io/en/latest/what_is_biocontainers.html |
BioContainers is a project that provides bioinformatics tools and workflows in a containerized format, making it easier to package, distribute, and run bioinformatics software in a reproducible manner. | Containerized Bioinformatics Tools & Workflows, Facilitates Reproducibility In Bioinformatics Analyses, Enables Easy Packaging & Distribution Of Bioinformatics Software, Supports Multiple Container Technologies Like Docker & Singularity | https://biocontainers-edu.readthedocs.io/en/latest/ | Containerization | Sciences | Biology | Bioinformatics, Containers, Reproducibility, Software Packaging, Workflow Management | https://biocontainers.pro/ | Biological Sciences | https://biocontainers-edu.readthedocs.io/en/latest/examples.html | Anvil: https://www.rcac.purdue.edu/software/biocontainers Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Anvil: Default Stampede-3: 0.1.0 |
Bioinformatics Tools | |
bioconvert | Anvil | Bioconvert is a collaborative project to facilitate the interconversion of life science data from one format to another. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bioconvert/bioconvert.html |
Bioconvert is a tool for converting between different bioinformatics file formats. It supports a wide range of formats commonly used in bioinformatics analysis and allows for easy and efficient conversion from one format to another. | 1. Conversion between various bioinformatics file formats.\r 2. Support for common formats such as FASTA, FASTQ, SAM, BAM, BED, VCF, and more.\r 3. Command-line interface for batch processing of files.\r 4. Efficient and reliable conversion process.\r 5. Customizable options for format conversion. |
https://bioconvert.readthedocs.io/en/dev/ | Converter | Sciences | Biology | Bioinformatics, Data Conversion, File Format | https://github.com/bioconvert/bioconvert | Biological Sciences | https://bioconvert.readthedocs.io/en/dev/tutorial.html | Anvil: https://www.rcac.purdue.edu/software/bioconvert | Anvil: 0.4.3, 0.5.2, 0.6.1, 0.6.2 | Utility Tool | |
bioformats | Bridges-2 | Bio-Formats is a software tool for reading and writing image data using standardized, open formats. Description Source: https://www.openmicroscopy.org/bio-formats/ |
Bioformats is a software library that provides reading and writing support for a wide range of biological data formats. It aims to simplify the access and integration of diverse image data types in scientific research. | 1. Reading and writing support for various biological image formats.\r 2. Ability to convert between different image data formats.\r 3. Efficient handling of large and complex image datasets.\r 4. Integration with popular programming languages and analysis tools. |
https://bio-formats.readthedocs.io/en/v7.3.0/ | Library | Sciences | Biology | Bioinformatics, Imaging, Biological Data, Data Formats | https://www.openmicroscopy.org/bio-formats/ | Biological Sciences | https://bio-formats.readthedocs.io/en/v7.3.0/about/index.html#help | Bridges-2: https://www.psc.edu/resources/software/bioformats | Bridges-2: 6.10.1 | Bioinformatics | |
biom-format | Faster | The BIOM file format (canonically pronounced biome) is designed to be a general-use format for representing biological sample by observation contingency tables. BIOM is a recognized standard for the Earth Microbiome Project and is a Genomics Standards Consortium supported project. Desciption Source: https://biom-format.org/ | BIOM (Biological Observation Matrix) format is a unified format to store biological sequence data, sample data, and observed taxonomic units. It provides a standard mechanism to represent, store, and share data generated by different high-throughput technologies such as marker gene surveys. | Standardized Format For Biological Data, Supports Storage Of Biological Sequence Data, Sample Metadata, & Taxonomic Unit Information, Facilitates Sharing & Integration Of Data From Different High-Throughput Technologies | https://biom-format.org/documentation/index.html | Data Management Tool | Genomics | Bioinformatics | Biological Data, High-Throughput Technologies, Data Sharing | https://biom-format.org/ | Biological Sciences | https://biom-format.org/documentation/quick_usage_examples.html#examples https://biom-format.org/documentation/table_objects.html#examples |
Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.1.12 | Data Format | |
bioperl | Aces, Faster | The Bioperl Project is an international association of users & developers of open source Perl tools for bioinformatics, genomics and life science. Description Source: https://bioperl.org/index.html |
BioPerl is a collection of Perl modules that provide an easy-to-use and comprehensive toolkit for bioinformatics tasks. It is specifically designed to assist biologists in writing code to analyze biological data and perform various bioinformatics tasks. | Parsing & Manipulation Of Sequence Data (DNA, RNA, Proteins), Sequence Alignment, Sequence Search & Retrieval From Databases, Phylogenetic Analysis Tools, Structure Analysis Tools, Interface With Other Bioinformatics Tools & Databases | https://bioperl.org/howtos/index.html | Library | Bioinformatics | Genetics | Bioinformatics, Computational Biology, Sequence Analysis, Perl | https://bioperl.org/index.html | Biological Sciences | https://github.com/bioperl/bioperl-live/tree/master/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.7.8 Faster: 1.7.2, 1.7.8 |
Bioinformatics Tool | |
biopython | Aces, Anvil, Faster | Biopython is a set of freely available tools for biological computation written in Python by an international team of developers. Description Source: https://biopython.org/ |
Biopython is a set of freely available tools for biological computation written in Python. It provides functionalities for molecular biology, bioinformatics, structural bioinformatics, and computational biology. | Sequence & Structure Manipulation, File Parsing (E.G., Fasta, Genbank), Blast, Ncbi Entrez Utilities, Phylogenetics & Population Genetics, Protein Structure Analysis, Sequence Motif Discovery | https://biopython.org/wiki/Documentation | Python Library | Molecular Biology | Bioinformatics | Biological Computation, Bioinformatics, Computational Biology, Molecular Biology, Structural Bioinformatics | https://biopython.org/ | Biological Sciences | https://biopython.org/DIST/docs/tutorial/Tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/biopython Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.79, 1.81, 1.82 Anvil: 1.70-Np112Py27, 1.70-Np112Py36, 1.78 Faster: 1.75-Python-3.7.4, 1.78, 1.79 |
Library | |
bismark | Anvil, Bridges-2, Expanse | Bismark is a program to map bisulfite treated sequencing reads to a genome of interest and perform methylation calls in a single step. The output can be easily imported into a genome viewer, such as SeqMonk, and enables a researcher to analyse the methylation levels of their samples straight away. Description Source: https://www.bioinformatics.babraham.ac.uk/projects/bismark/ |
Bismark is a software tool specifically designed for aligning bisulfite treated DNA sequencing reads and methylation calls. It is widely used in epigenetics research to analyze DNA methylation patterns. | 1. Alignment of bisulfite treated DNA sequencing reads\r 2. Identification of methylated cytosines\r 3. Differential methylation analysis\r 4. Visualization of methylation patterns\r 5. Compatibility with various sequencing platforms and data formats |
https://felixkrueger.github.io/Bismark/ | Alignment & Methylation Analysis | Epigenetics | Genomics | Epigenetics, DNA Methylation, Bisulfite Sequencing, Genomics, Bioinformatics | https://www.bioinformatics.babraham.ac.uk/projects/bismark/ | Biological Sciences | https://felixkrueger.github.io/Bismark/bismark/ | Anvil: https://www.rcac.purdue.edu/software/bismark Bridges-2: https://www.psc.edu/resources/software/bismark Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 0.23.0, 0.24.0 Bridges-2: 0.22.3 Expanse: 4Xdflxj |
Bioinformatics | |
bison | Aces, Faster, Ookami | Bison is a general-purpose parser generator that converts an annotated context-free grammar into a deterministic LR or generalized LR (GLR) parser employing LALR(1) parser tables. Description Source: https://www.gnu.org/software/bison/ |
Bison is a general-purpose parser generator that converts a grammar description for an LALR context-free grammar into a C program to parse that grammar. It is part of the GNU Project. | Bison generates bottom-up parsers. It helps in constructing parsers for programming languages and other complex data description languages. | https://www.gnu.org/software/bison/manual/bison.html | Parser Generator | General | General | Parser Generator, Programming Language Tool | https://www.gnu.org/software/bison/ | Computer & Information Sciences | https://www.gnu.org/software/bison/manual/html_node/Examples.html https://aquamentus.com/flex_bison.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 3.3.2, 3.7.1, 3.7.6, 3.8.2 Faster: 3.0.4, 3.0.5, 3.3.2, 3.5.3, 3.7.1, 3.7.6, 3.8.2 Ookami: 3.8.1 |
Development Tools | |
blacs | Darwin | The BLACS (Basic Linear Algebra Communication Subprograms) project is an ongoing investigation whose purpose is to create a linear algebra oriented message passing interface that may be implemented efficiently and uniformly across a large range of distributed memory platforms. Description Source: https://www.netlib.org/blacs/ |
The Basic Linear Algebra Communication Subprograms (BLACS) is a collection of routines for dense linear algebra operations that can be used to construct parallel linear algebra software libraries. BLACS is typically used in high-performance computing environments to efficiently solve large-scale linear algebra problems in parallel. | 1. Enables the development of parallel linear algebra libraries\r 2. Optimized for high-performance computing environments\r 3. Support for various matrix operations and parallel communication\r 4. Efficiently handles large-scale linear algebra problems |
https://www.netlib.org/blacs/ | Computational Software | Computer Science, Engineering | Mathematics | Linear Algebra, High-Performance Computing, Parallel Computing | https://www.netlib.org/blacs/ | Physical Sciences | https://www.netlib.org/blacs/BLACS/Examples.html | Library | |||
blasr | Anvil | Blasr is a read mapping program that maps reads to positions in a genome by clustering short exact matches between the read and the genome, and scoring clusters using alignment. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/blasr/blasr.html |
BLASR is a software tool designed for aligning SMRT sequencing reads to a reference genome. It is developed by Pacific Biosciences and provides accurate mapping of long and noisy reads. | Key features of BLASR include alignment of long reads with high error rates, compatibility with Pacific Biosciences sequencing data, support for various input formats such as HDF5 and FASTQ, and customizable parameters for optimization. | https://www.pacb.com/wp-content/uploads/SMRT-Tools-Reference-Guide-v8.0.pdf | Mapping | Sciences | Biology | Alignment, Sequencing, Genomics | https://github.com/PacificBiosciences/blasr | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/blasr | Anvil: 5.3.5 | Alignment | ||
blast | Anvil, Bridges-2, Faster | BLAST (Basic Local Alignment Search Tool) finds regions of similarity between biological sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/blast/blast.html |
BLAST (Basic Local Alignment Search Tool) is a powerful bioinformatics software tool used to search for homologous sequences in protein and nucleotide databases. It compares a query sequence against a chosen sequence database and identifies local sequence similarities. | 1. High-speed sequence comparison\r 2. Database search capability\r 3. Alignment of query sequences with database sequences\r 4. Identifying homologous sequences\r 5. Various search parameters for customization |
https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/doxyhtml/group__AlgoBlast.html | Sequence Analysis Tool | Bioinformatics | Biological Sciences | Bioinformatics, Sequence Alignment, Homology Search | https://blast.ncbi.nlm.nih.gov/Blast.cgi | Biological Sciences | https://blast.ncbi.nlm.nih.gov/doc/blast-quick-start-guide/ https://www.youtube.com/playlist?list=PL7dF9e2qSW0azL2xOKAtxDW7QI8UU4XZ6 |
Anvil: https://www.rcac.purdue.edu/software/blast Bridges-2: https://www.psc.edu/resources/software/blast Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 2.11.0, 2.13.0 Bridges-2: 2.9.0, 2.11.0 Faster: 2.11.0-Linux_X86_64 |
Bioinformatics Tool | |
blast-plus | Anvil, Expanse | Blast+ allows users to perform BLAST searches on their own server without size, volume and database restrictions. BLAST+ can be used with a command line so it can be integrated directly into your workflow. Description Source: https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html |
https://github.com/ncbi/blast_plus_docs | Tool | Sciences | Biology | https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html | https://github.com/ncbi/blast_plus_docs?tab=readme-ov-file#section-2---a-step-by-step-guide-using-the-blast-docker-image | Anvil: https://www.rcac.purdue.edu/software/blast-plus Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 2.12.0 Expanse: Jrvhcsy |
Bioinformatics, Developer Support | |||||
blast+ | Aces, Faster, Ookami | Blast+ allows users to perform BLAST searches on their own server without size, volume and database restrictions. BLAST+ can be used with a command line so it can be integrated directly into your workflow. Description Source: https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html |
BLAST+ (Basic Local Alignment Search Tool) is a suite of tools for performing similarity searches of nucleotide and protein databases. It is widely used for comparing biological sequences to identify homologous sequences and infer functional and evolutionary relationships. | Search Nucleotide & Protein Databases For Similarity, Identify Homologous Sequences, Infer Functional & Evolutionary Relationships, Highly Efficient Search Algorithms | https://github.com/ncbi/blast_plus_docs | Bioinformatics Tool | Genomics | Bioinformatics | Bioinformatics, Computational Biology, Genomics, Sequence Analysis | https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html | Biological Sciences | https://github.com/ncbi/blast_plus_docs?tab=readme-ov-file#section-2---a-step-by-step-guide-using-the-blast-docker-image | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 2.13.0, 2.14.1 Faster: 2.9.0, 2.12.0, 2.13.0 Ookami: Gcc8/2.12.0 |
Search & Alignment Tool | |
blat | Bridges-2, Expanse | BLAT on DNA is designed to quickly find sequences of 95% and greater similarity of length 25 bases or more. It may miss more divergent or shorter sequence alignments. It will find perfect sequence matches of 20 bases. Description Source: https://genome.ucsc.edu/cgi-bin/hgBlat |
BLAT (BLAST-Like Alignment Tool) is a sequence analysis software used for comparing genomic DNA sequences to the human genome. It is particularly useful for finding regions of similarity between DNA sequences at the nucleotide level. | 1. Rapid alignment of DNA sequences\r 2. Ability to handle large genomes\r 3. Identifying regions of similarity at the nucleotide level\r 4. Support for genome mapping and finding gene structures\r 5. User-friendly interface |
https://kentinformatics.com/documentation | Tool | Sciences | Biology | Sequence Analysis, DNA Alignment, Genomic Analysis | https://kentinformatics.com/ | Biological Sciences | https://genome.ucsc.edu/training/index.html | Bridges-2: https://www.psc.edu/resources/software/blat Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Bridges-2: 36 Expanse: 35 |
Bioinformatics | |
blender | Aces, Faster | Blender is the free and open source 3D creation suite. It supports the entirety of the 3D pipeline—modeling, rigging, animation, simulation, rendering, compositing and motion tracking, even video editing and game creation. Description Source: https://www.blender.org/about/ |
Blender is a free and open-source 3D creation suite that supports the entire 3D pipeline – modeling, rigging, animation, simulation, rendering, compositing and motion tracking, even video editing and game creation. | 3D Modeling, Animation, Simulation, Rendering, Game Creation, Video Editing, Compositing | https://docs.blender.org/manual/en/latest/ | Visual Arts Software | General | General | 3D Modeling, Computer Graphics, Animation, Simulation, Open-Source | https://www.blender.org/ | Engineering & Technology | https://www.youtube.com/watch?v=TPrnSACiTJ4&list=PLjEaoINr3zgHs8uzT3yqe4iHGfkCmMJ0P https://en.wikibooks.org/wiki/Blender_3D:_Noob_to_Pro |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.5.0-Linux-X86_64-Cuda-11.7.0 Faster: 3.0.0-Linux-X64, 3.1.2-Linux-X64 |
3D Modeling & Animation | |
blis | Aces, Anvil, Darwin, Faster, Ookami | BLIS is an award-winning portable software framework for instantiating high-performance BLAS-like dense linear algebra libraries. Description Source: https://github.com/flame/blis |
BLAS (Basic Linear Algebra Subprograms) implemented in native C and suitable for high-performance implementations. BLIS is capable of achieving high levels of performance on various architectures. | High-performance BLAS library, portable and flexible, optimized for various modern architectures, includes a BLISlab for automated performance analysis and tuning. | https://github.com/flame/blis/blob/master/docs/BLISTypedAPI.md | Computational Software | Engineering | Mathematics | Blas, Linear Algebra, High Performance Computing, Optimization | https://github.com/flame/blis | Computer & Information Sciences | https://github.com/flame/blis/blob/master/docs/Testsuite.md https://github.com/flame/blis/tree/master/examples/oapi |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/blis Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 0.8.1, 0.9.0 Anvil: 0.8.1 Faster: 0.8.0, 0.8.1, 0.9.0, 2.2-Amd, 3.1-Amd Ookami: Gcc12.1.0/0.9.0 |
Library | |
blobtools | Anvil | Blobtools is a modular command-line solution for visualisation, quality control and taxonomic partitioning of genome datasets. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/blobtools/blobtools.html |
BlobTools is a software suite for visualizing and analyzing genome assembly data. It allows users to assess the quality and taxonomic composition of a genome assembly using data generated from short-read sequencing technologies. | Some of the core features of BlobTools include taxon assignment, assessment of genome completeness, visualization of assembly statistics, and exploration of metagenomic datasets. | https://blobtools.readme.io/docs/what-is-blobtools | Bioinformatics Tool | Sciences | Biology | Genome Assembly, Data Visualization, Metagenomics | https://github.com/DRL/blobtools | Biological Sciences | https://blobtools.readme.io/docs/my-first-blobplot | Anvil: https://www.rcac.purdue.edu/software/blobtools | Anvil: 1.1.1 | Visualization & Analysis | |
blosc2 | Aces, Faster | Blosc, an extremely fast, multi-threaded, meta-compressor library. Description Source: https://www.blosc.org/pages/ |
Blosc2 is a high-performance, production-ready meta-compressor library that provides a simple way to accelerate data storage and retrieval. It focuses on optimizing the handling of large, multi-dimensional data, catering to both compression and decompression operations efficiently. | 1. Multi-dimensional data support\r 2. High-performance compression and decompression\r 3. Production-ready meta-compressor library\r 4. Data storage and retrieval optimization\r 5. Supported by various programming languages\r 6. Parallel compression with thread and process-based approaches |
https://www.blosc.org/c-blosc2/c-blosc2.html | Compression | General | General | High-Performance Computing, Compression, Data Storage, Optimization | https://github.com/Blosc/c-blosc2 | Computer & Information Sciences | https://github.com/Blosc/c-blosc2/tree/main/examples https://www.youtube.com/watch?v=ER12R7FXosk |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.4.3 Faster: 2.4.3 |
Library | |
bmge | Anvil | Bmge is a program that selects regions in a multiple sequence alignment that are suited for phylogenetic inference. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bmge/bmge.html |
BMGE (Block Mapping and Gathering with Entropy) is a software tool designed for the alignment of homologous DNA or protein sequences. It employs block mapping and entropy-based techniques to identify and remove poorly aligned regions, thereby improving the accuracy of multiple sequence alignments. | Alignment Of Homologous DNA Or Protein Sequences, Utilizes Block Mapping & Entropy-Based Techniques, Identification & Removal Of Poorly Aligned Regions, Improves Accuracy Of Multiple Sequence Alignments | https://gensoft.pasteur.fr/docs/BMGE/1.12/ | Sequence Alignment Tool | Sequence Analysis | Bioinformatics | Bioinformatics, Computational Biology, Sequence Alignment, Sequence Analysis | https://bio.tools/bmge | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/bmge | Anvil: 1.12 | Bioinformatics Tool | ||
bohrium | Faster | Bohrium provides automatic acceleration of array operations in Python/NumPy, C, and C++ targeting multi-core CPUs and GP-GPUs. Forget handcrafting CUDA/OpenCL to utilize your GPU and forget threading, mutexes and locks to utilize your multi-core CPU, just use Bohrium! Description Source: https://bohrium.readthedocs.io/index.html |
Bohrium is a high-performance JIT-compiled array programming language that extends Python with support for versatile array operations using a subset of the APL syntax. It automatically parallelizes and runs programs on the CPU and GPU. | 1. Python integration with APL-like array operations. 2. Just-in-time (JIT) compilation for high performance. 3. Automatic parallelization for CPU and GPU execution. 4. Seamless integration with existing Python libraries and tools. | https://bohrium.readthedocs.io/index.html | High-Performance Computing Tool | Programming Languages & Compilers | Computer Science | High-Performance Computing, Array Programming, Python Integration, Gpu Acceleration | https://github.com/bh107/bohrium | Computer & Information Sciences | https://bohrium.readthedocs.io/users/cpp.html#code-snippets | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.11.0.Post60 | Array Programming Language | |
bokeh | Aces, Faster | Bokeh is a Python library for creating interactive visualizations for modern web browsers. It helps you build beautiful graphics, ranging from simple plots to complex dashboards with streaming datasets. Description Source: https://docs.bokeh.org/en/latest/ |
Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics with high-performance interactivity over large or streaming datasets in a browser window. | Some core features of Bokeh include creating versatile plots, dashboards, and data applications in Python; interactive visualizations with a large selection of visual elements such as plots, tables, and sliders; seamless integration with Jupyter notebooks; support for streaming and real-time data; and the ability to create interactive, web-ready plots which can be easily shared. | https://docs.bokeh.org/en/latest/ | Library | General | General | Visualization, Interactive Plots, Data Visualization | https://bokeh.org/ | Computer & Information Sciences | https://realpython.com/python-data-visualization-bokeh/ https://programminghistorian.org/en/lessons/visualizing-with-bokeh |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.4.1, 2.4.2, 2.4.3 Faster: 1.4.0-Python-3.7.4, 2.0.2-Python-3.8.2, 2.2.3, 2.4.2, 2.4.3 |
Visualization | |
boost | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Kyric, Ookami, Stampede3 | BLAST (Basic Local Alignment Search Tool) is a bioinformatics software program used for comparing primary biological sequence information, such as the amino-acid sequences of proteins or the nucleotides of DNA and/or RNA sequences. It's widely used for identifying similarities, understanding evolutionary relationships, and finding functional and structural homologues among sequences in large databases, making it a crucial tool in genomic and proteomic research. | Boost is a set of C++ libraries that provides support for tasks and structures such as linear algebra, pseudorandom number generation, multithreading, image processing, regular expressions, and unit testing. It aims to extend the functionality of C++ programming language and make it more efficient and powerful. | Extensive C++ Libraries, Support For Various Tasks & Data Structures, Enhanced Functionality For C++ Programming | https://www.boost.org/doc/libs/1_84_0/ | Development Tool | Engineering | Computer Science, Software Engineering, Systems, & Development | C++ Libraries, Programming Support, Efficiency Enhancement | https://www.boost.org/ | Computer & Information Sciences | https://www.boost.org/doc/libs/1_77_0/more/getting_started/index.html https://theboostcpplibraries.com/ |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/boost Bridges-2: https://www.psc.edu/resources/software/boost Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 1.76.0, 1.77.0, 1.79.0, 1.81.0, 1.82.0, 1.83.0 Anvil: 1.74.0 Bridges-2: 1.75-Gcc10.2.0, 1.75.0-Intel20.4 Delta: 1.83.0 Expanse: Bbnd4Wn, Ckwq57R, ... Faster: 1.71.0, 1.72.0, 1.74.0, 1.76.0, 1.77.0, 1.79.0, 1.81.0, 1.82.0 Kyric: 1.73.0 Ookami: Gcc8.5/1.83 Stampede-3: 1.85.0 |
Library | |
boost.mpi | Aces | Boost.MPI is a library for message passing in high-performance parallel applications. Description Source: https://www.boost.org/doc/libs/1_84_0/doc/html/mpi/tutorial.html |
Boost.MPI is a peer-reviewed, free, open-source, portable, and fully-standard library implementation of the Message Passing Interface (MPI) for C++. | Boost.MPI provides an intuitive C++ interface for MPI operations, allowing for seamless integration of parallelism into C++ applications. It offers support for point-to-point and collective communication, synchronizations, and parallel computational operations. | https://www.boost.org/doc/libs/1_84_0/doc/html/mpi.html | Middleware | Software Engineering, Systems, & Development | Other Computer & Information Sciences | Mpi, Parallel Computing, C++ | https://github.com/boostorg/mpi | Computer & Information Sciences | https://www.boost.org/doc/libs/1_84_0/doc/html/mpi/tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.79.0 | Library | |
boost.python | Aces, Faster | Boost.Python is a C++ library which enables seamless interoperability between C++ and the Python programming language. Description Source: https://www.boost.org/doc/libs/1_84_0/libs/python/doc/html/index.html |
Boost.Python is a library used for interfacing Python and C++. It enables seamless integration of C++ code with Python and provides tools to expose C++ classes, functions, and objects to Python scripts, and vice versa. | Bi-Directional Communication Between C++ & Python, Automatic Mapping Of Basic C++ Types To Python, Support For Exposing C++ Classes, Functions, & Modules To Python, Ability To Call Python Code From C++ & Vice Versa, Extensive Documentation & Community Support | https://www.boost.org/doc/libs/1_84_0/libs/python/doc/html/index.html | Library | Engineering | Mathematics | C++, Python, Integration, Library | https://github.com/boostorg/python | Computer & Information Sciences | https://boostorg.github.io/python/doc/html/tutorial/index.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.79.0, 1.81.0, 1.83.0 Faster: 1.71.0, 1.76.0, 1.77.0, 1.81.0 |
Scientific Library | |
botorch | Faster | BoTorch (pronounced "bow-torch" / ˈbō-tȯrch) is a library for Bayesian Optimization research built on top of PyTorch, and is part of the PyTorch ecosystem. Description Source: https://botorch.org/docs/introduction |
BoTorch is a library for Bayesian optimization built on PyTorch. It provides a modular and scalable approach to Bayesian optimization, including state-of-the-art methods for acquisition functions, models, and optimizers, all implemented in PyTorch. | Modular & Scalable Approach To Bayesian Optimization, State-Of-The-Art Methods For Acquisition Functions, Models, & Optimizers, Implemented In Pytorch For Seamless Integration With Deep Learning Workflows | https://botorch.org/docs/introduction | Bayesian Optimization Library | Machine Learning | Artificial Intelligence & Intelligent Systems | Bayesian Optimization, Pytorch, Machine Learning | https://botorch.org/ | Computer & Information Sciences | https://botorch.org/tutorials/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.6.0-Python-3.8.6 | Computational Library | |
bottleneck | Faster | Bottleneck is a collection of fast NumPy array functions written in C. Description Source: https://github.com/pydata/bottleneck |
bottleneck is a collection of fast NumPy array functions written in C. It is designed to work in situations where speed is important, particularly for large data sets. | 1. Fast NumPy array functions\r 2. Optimized for performance\r 3. Ideal for large data sets\r 4. Written in C for efficiency |
https://bottleneck.readthedocs.io/en/latest/ | Data Processing | Sciences, Engineering | Computer Science, Mathematics | Numpy, Array Functions, Performance Optimization | https://github.com/pydata/bottleneck | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.3.2-Python-3.8.6, 1.3.2-Python-3.9.6 | Library | ||
bowtie | Anvil, Faster | Bowtie is an ultrafast, memory-efficient short read aligner geared toward quickly aligning large sets of short DNA sequences (reads) to large genomes. Description Source: https://bowtie-bio.sourceforge.net/manual.shtml |
Bowtie is a fast and memory-efficient short read aligner for short DNA sequences. It aligns short DNA sequences (reads) to the human genome at a rate of over 25 million reads per hour on a typical workstation with a large amount of memory. | Some core features of Bowtie include ultrafast alignment, memory efficiency, support for gapped alignment, support for multi-core processing, and compatibility with various sequencing platforms. | https://bowtie-bio.sourceforge.net/manual.shtml | Alignment Tool | Biological Sciences | Genetics | Bioinformatics, Genomics, DNA Sequencing, Sequence Alignment | https://bowtie-bio.sourceforge.net/index.shtml | Biological Sciences | https://bowtie-bio.sourceforge.net/tutorial.shtml | Anvil: https://www.rcac.purdue.edu/software/bowtie Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 1.3.1 Faster: 1.3.1 |
Bioinformatics | |
bowtie2 | Anvil, Bridges-2, Expanse, Faster | Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning to relatively long (e.g. mammalian) genomes. Description Source: https://github.com/BenLangmead/bowtie3 |
Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly well-suited for aligning sequencing reads of DNA sequences, such as those generated by high-throughput sequencing technologies. | Ultrafast Alignment Of Sequencing Reads To Long Reference Sequences, Memory-Efficient Indexing & Alignment Process, Support For Gapped, Local, & End-To-End Alignment Modes, Alignment & Mapping Of DNA Sequencing Reads, High Accuracy In Finding Alignments, Scalability For Large Genomes & Datasets | https://bowtie-bio.sourceforge.net/bowtie2/manual.shtml | Sequence Alignment | Genomics | Bioinformatics | Alignment, Sequencing Reads, DNA Sequences, High-Throughput Sequencing, Bioinformatics, Genomics | https://bowtie-bio.sourceforge.net/bowtie2/index.shtml | Biological Sciences | https://bowtie-bio.sourceforge.net/bowtie2/manual.shtml#getting-started-with-bowtie-2-lambda-phage-example | Anvil: https://www.rcac.purdue.edu/software/bowtie2 Bridges-2: https://www.psc.edu/resources/software/bowtie2 Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 2.4.2, 2.5.1 Bridges-2: 2.4.2, 2.4.4 Expanse: Ahg6M6S Faster: 2.4.4, 2.4.5, 2.5.1 |
Alignment Tool | |
bracken | Anvil | Bracken (Bayesian Reestimation of Abundance with KrakEN) is a highly accurate statistical method that computes the abundance of species in DNA sequences from a metagenomics sample. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bracken/bracken.html |
Bracken is a tool that utilizes a Bayesian framework to estimate species abundance from metagenomic data generated by sequencing. It is particularly useful in the analysis of microbial communities and microbiome data. | Estimates Species Abundance From Metagenomic Data, Utilizes A Bayesian Framework, Useful For Analyzing Microbial Communities & Microbiome Data | https://ccb.jhu.edu/software/bracken/index.shtml?t=manual | Tool | Metagenomics | Microbial Ecology | Metagenomics, Microbiome, Species Abundance Estimation, Bayesian Analysis | https://github.com/jenniferlu717/Bracken | Biological Sciences | https://github.com/jenniferlu717/Bracken?tab=readme-ov-file#example-abundance-estimation | Anvil: https://www.rcac.purdue.edu/software/bracken | Anvil: 2.6.1, 2.7 | Bioinformatics | |
braker2 | Anvil | BRAKER is a pipeline for fully automated prediction of protein coding gene structures with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/braker2/braker2.html |
BRAKER2 is a novel tool for unsupervised RNA-Seq-based genome annotation. It combines gene prediction and RNA-Seq alignment in an innovative and computational efficient way to improve genome annotations. | 1. Unsupervised training process for gene prediction based on RNA-Seq data. 2. Integration of RNA-Seq data to improve gene prediction accuracy. 3. Support for both eukaryotic and prokaryotic genomes. 4. High computational efficiency compared to traditional genome annotation tools. | https://bioinf.uni-greifswald.de/augustus/binaries/tutorial2018/BRAKER_userguide.pdf | Genome Annotation Tool | Bioinformatics | Biological Sciences | Genome Annotation, RNA-Seq Data, Gene Prediction | https://github.com/Gaius-Augustus/BRAKER | Biological Sciences | https://www.youtube.com/watch?v=UXTkJ4mUkyg | Anvil: https://www.rcac.purdue.edu/software/braker2 | Anvil: 2.1.6 | Computational Software | |
brass | Anvil | Brass is used to analyze one or more related BAM files of paired-end sequencing to determine potential rearrangement breakpoints. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/brass/brass.html |
Brass is a circuit design and simulation software that allows users to create, edit, and simulate electronic circuits. It provides a user-friendly interface for designing and testing circuits for various applications. | Circuit Design, Simulation, Electronic Components Library, User-Friendly Interface | https://github.com/cancerit/BRASS | Circuit Design & Simulation | Sciences | Biology | Circuit Design, Electronic Simulation, Electronics | https://github.com/cancerit/BRASS | Engineering & Technology | Anvil: https://www.rcac.purdue.edu/software/brass | Anvil: 6.3.4 | Simulation Software | ||
breseq | Anvil | Breseq is a computational pipeline for the analysis of short-read re-sequencing data. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/breseq/breseq.html |
Breseq is a computational tool for identifying mutations in bacteria that have evolved in a microbial population. It can detect single nucleotide variants, insertions, deletions, inversions, and complex polymorphisms in bacterial genomes. | 1. Identification of mutations in bacterial genomes\r 2. Detection of single nucleotide variants, insertions, deletions, inversions, and complex polymorphisms\r 3. Visualization of identified mutations\r 4. Analysis of microbial evolution within a population |
https://barricklab.org/twiki/pub/Lab/ToolsBacterialGenomeResequencing/documentation/ | Genome Analysis Tool | Microbial Genetics | Genetics | Computational Biology, Bioinformatics, Genomics | https://github.com/barricklab/breseq | Biological Sciences | https://barricklab.org/twiki/pub/Lab/ToolsBacterialGenomeResequencing/documentation/tutorial_clones.html https://barricklab.org/twiki/pub/Lab/ToolsBacterialGenomeResequencing/documentation/tutorial_populations.html https://barricklab.org/twiki/pub/Lab/ToolsBacterialGenomeResequencing/documentation/tutorial_barcoded_targeted.html |
Anvil: https://www.rcac.purdue.edu/software/breseq | Anvil: 0.36.1 | Bioinformatics Tool | |
brotli | Aces, Faster | Brotli is a generic-purpose lossless compression algorithm that compresses data using a combination of a modern variant of the LZ77 algorithm, Huffman coding and 2nd order context modeling, with a compression ratio comparable to the best currently available general-purpose compression methods. Description Source: https://brotli.org/ |
Brotli is a generic-purpose lossless compression algorithm that compresses data using a combination of a modern variant of the LZ77 algorithm, Huffman coding, and 2nd order context modelling. It is developed by Google and designed to replace the zlib compression. | 1. High compression ratio: Brotli provides better compression ratios compared to the existing compression algorithms. 2. Fast decompression speed: Brotli decompression is highly efficient, making it suitable for use in various applications. 3. Support for multiple platforms: Brotli is available for various platforms including desktop and mobile environments. 4. Open-source: Brotli is an open-source project, allowing for community contributions and improvements. 5. Integration with web browsers: Brotli is supported by major web browsers, enabling faster loading times for web pages. | https://github.com/google/brotli | Tool | General | General | Compression Algorithm, Lossless Compression, Data Compression | https://brotli.org/ | https://kinsta.com/blog/brotli-compression/ | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.0.9 Faster: 1.0.9 |
Developer Support | ||
brotli-python | Aces | Brotli is a generic-purpose lossless compression algorithm that compresses data using a combination of a modern variant of the LZ77 algorithm, Huffman coding and 2nd order context modeling, with a compression ratio comparable to the best currently available general-purpose compression methods. Description Source: https://brotli.org/ |
brotli-python is a Python binding for the Brotli compression library. It allows users to compress and decompress data using the Brotli algorithm within Python applications. | 1. Compression and decompression of data using the Brotli algorithm.\r 2. Integration with Python applications for efficient data compression.\r 3. Support for various compression levels and settings.\r 4. High compression ratio and fast decompression speed. |
https://python-hyper.org/projects/brotlipy/en/latest/ | Compression Library | Data Compression | Computer Science | Compression, Data Compression, Brotli, Python Library | https://github.com/python-hyper/brotlicffi | Computer & Information Sciences | https://github.com/python-hyper/brotlicffi/tree/main/example | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.0.9 | Library | |
brunsli | Aces, Faster | Brunsli is a lossless JPEG repacking library. Brunsli allows for a 22% decrease in file size while allowing the original JPEG to be recovered byte-by-byte. Description Source: https://github.com/google/brunsli |
Brunsli is an advanced lossless image compressor that focuses on high-speed encoding. It aims to achieve significant compression ratios while maintaining fast encoding and decoding speeds. | 1. Lossless image compression\r 2. High-speed encoding\r 3. Efficient compression ratios\r 4. Fast decoding speeds |
https://github.com/google/brunsli | Image Compressor | General | General | Image Compression, Lossless Compression, High-Speed Encoding | https://brunsli.dev/ | Computer & Information Sciences | https://github.com/google/brunsli?tab=readme-ov-file#build-instructions | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.1 Faster: 0.1 |
Compression Software | |
build | Faster | A simple, correct Python build frontend. Description Source: https://github.com/pypa/build |
Build is a task automation tool that allows users to define tasks in a buildfile. It is commonly used for compiling source code, running tests, creating distributions, and other repetitive tasks in software development projects. | Task Automation, Buildfile Configuration, Dependency Management, Plugin System, Integration With Version Control Systems | https://build.pypa.io/en/stable/ | Task Automation | General | General | Task Automation, Build Tool, Software Development | https://github.com/pypa/build | Engineering & Technology | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.10.0 | Development Tools | ||
busco | Anvil, Bridges-2 | Benchmarking Universal Single-Copy Orthologs (BUSCO) is used for assessing genome assembly and annotation completeness. Description Source: https://gitlab.com/ezlab/busco |
BUSCO (Benchmarking Universal Single-Copy Orthologs) is a software package that assesses genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content. | 1. Evaluation of genome assembly and gene or protein set completeness. 2. Benchmarking against evolutionarily-informed expectations. 3. Analysis of orthologous genes or proteins. 4. Scalable and versatile for different organisms. | https://busco.ezlab.org/busco_userguide.html | Tools | Genomics | Bioinformatics | Genomics, Genome Assembly, Gene Set, Transcriptome, Orthologs | https://busco.ezlab.org/ | Biological Sciences | https://busco.ezlab.org/busco_userguide.html#running-busco | Anvil: https://www.rcac.purdue.edu/software/busco Bridges-2: https://www.psc.edu/resources/software/busco |
Anvil: 5.2.2, 5.3.0, 5.4.1, 5.4.3, 5.4.4, 5.4.5, 5.4.7 Bridges-2: 5.0.0 |
Computational Biology | |
bustools | Anvil | Bustools is a program for manipulating BUS files for single cell RNA-Seq datasets. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bustools/bustools.html |
bustools is a software package for manipulating single-cell RNA-seq data and performing various analysis tasks such as mapping, quantification, error correction, and filtering. It is specifically designed for analyzing droplet-based single-cell RNA-seq data generated from technologies like 10X Genomics' Chromium platform. | Mapping Reads To A Reference Genome, Quantifying Unique Molecular Identifiers (Umis), Filtering Input Data Based On Quality Metrics, Error Correcting Umis For Greater Accuracy, Clustering Cells & Analyzing Expression Profiles | https://bustools.github.io/manual | Bioinformatics Tool | Genomics | Bioinformatics | Single-Cell RNA-Seq, Data Analysis, Bioinformatics, Computational Biology | https://bustools.github.io/ | Biological Sciences | https://www.kallistobus.tools/applications/ | Anvil: https://www.rcac.purdue.edu/software/bustools | Anvil: 0.41.0 | Data Analysis Tool | |
bwa | Aces, Anvil, Bridges-2, Expanse, Faster | BWA is a software package for mapping low-divergent sequences against a large reference genome, such as the human genome. Description Source: https://bio-bwa.sourceforge.net/ |
Burrows-Wheeler Aligner (BWA) is a software package for mapping low-divergent sequences against a large reference genome, such as the human genome. It consists of three algorithms: BWA-backtrack, BWA-SW, and BWA-MEM. The BWA-backtrack algorithm is designed for Illumina sequence reads up to 100bp, while BWA-SW and BWA-MEM are for longer Illumina reads, including 100bp reads produced by the HiSeq 2000 platform. | Mapping Low-Divergent Sequences, Alignment Of Illumina Sequence Reads, Support For Short & Long Reads, Efficient Memory Usage | https://bio-bwa.sourceforge.net/bwa.shtml | Bioinformatics Tool | Sciences | Biology | Sequence Alignment, Bioinformatics, Genomics, Next-Generation Sequencing (Ngs) | https://bio-bwa.sourceforge.net/ | Biological Sciences | https://bioinformatics-core-shared-training.github.io/cruk-bioinf-sschool/Day1/Sequence%20Alignment_July2015_ShamithSamarajiwa.pdf | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/bwa Bridges-2: https://www.psc.edu/resources/software/bwa Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.7.17 Anvil: 0.7.17 Bridges-2: 0.7.3A Expanse: 0.7.17 Faster: 0.7.17 |
Alignment Tool | |
bwameth | Anvil | Bwameth is a tool for fast and accurante alignment of BS-Seq reads. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/bwameth/bwameth.html |
Bwameth is a software tool designed for aligning bisulfite-treated sequencing reads (BS-Seq) from targeted bisulfite sequencing experiments with DNA methylation analysis. | The core features of bwameth include alignment of BS-Seq reads, detection of 5-methylcytosine bases, calculation of DNA methylation levels, and visualization of methylation patterns. | https://github.com/brentp/bwa-meth | Bioinformatics Tool | Epigenetics | Genetics | DNA Methylation, Bisulfite Sequencing, Alignment, Bioinformatics | https://github.com/brentp/bwa-meth | Biological Sciences | https://github.com/brentp/bwa-meth/tree/master/example/ | Anvil: https://www.rcac.purdue.edu/software/bwameth | Anvil: 0.2.5 | Sequence Alignment Tool | |
byacc | Expanse | Berkeley Yacc is an LALR(1) parser generator. Berkeley Yacc has been made as compatible as possible with AT&T Yacc. Berkeley Yacc can accept any input specification that conforms to the AT&T Yacc documentation. Description Source: https://github.com/grandseiken/byacc |
byacc is a public domain LALR parser generator which is often used as a replacement for yacc. LALR parsers are used in the generation of efficient parsers for modern programming languages. | byacc generates parsers for context-free grammars, assists in building syntax analysis for programming languages, facilitates the creation of efficient parsers for various applications. | https://invisible-island.net/byacc/manpage/yacc.html | Development Tool | General | General | Parser Generator, Lalr, Context-Free Grammar | https://invisible-island.net/byacc/ | Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Master | Compiler | ||
bzip2 | Aces, Expanse, Faster, Kyric | bzip2 is a freely available, patent free, high-quality data compressor. It typically compresses files to within 10% to 15% of the best available techniques (the PPM family of statistical compressors), whilst being around twice as fast at compression and six times faster at decompression. Description Source: https://sourceware.org/bzip2/ |
bzip2 is a free and open-source file compression program that uses the Burrows-Wheeler algorithm for compression and Huffman coding for decompression. It is designed to be fast and efficient in compressing large files while retaining a high compression ratio. | 1. High compression ratio\r 2. Fast compression and decompression speeds\r 3. Open-source and free to use\r 4. Cross-platform compatibility\r 5. Efficient use of system resources |
https://sourceware.org/bzip2/manual/manual.html | Compression Tool | General | General | File Compression, Data Compression, Utility Software | https://sourceware.org/bzip2/ | Computer & Information Sciences | https://www.tutorialspoint.com/unix_commands/bzip2.htm | Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.0.8 Expanse: 1.0.8 Faster: 1.0.6, 1.0.8 |
Utility | |
c-ares | Aces, Faster | c-ares is a C library for asynchronous DNS requests (including name resolves). Description Source: https://c-ares.org/ |
c-ares is a C library that performs DNS requests and name resolutions asynchronously. It is designed to be lightweight and efficient, providing asynchronous DNS capabilities to applications. | Asynchronous Dns Requests, Support For Ipv4 & Ipv6, Thread-Safe Design, Support For Multiple Dns Server Configurations, Compatible With Various Operating Systems | https://c-ares.org/docs.html | Networking | General | General | Dns, Asynchronous, Networking, Library, C | https://c-ares.org/ | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.18.1 Faster: 1.17.2, 1.18.1 |
Library | ||
cactus | Anvil | Cactus is a reference-free whole-genome alignment program, as well as a pagenome graph construction toolkit. Description Source = https://github.com/ComparativeGenomicsToolkit/cactus?tab=readme-ov-file | Cactus is an open-source software package designed for numerical relativity simulations within the Einstein field equations of general relativity. It provides a framework for solving partial differential equations on adaptive grids in high-performance computing environments. | 1. Solves partial differential equations\r 2. Supports adaptive grid techniques\r 3. Designed for numerical relativity simulations\r 4. Utilizes advanced high-performance computing environments |
https://www.cactuscode.org/documentation/ReferenceManual.pdf | Simulation Software | Numerical Relativity | Gravitational Physics | Computational Software, Hpc Tools | https://github.com/ComparativeGenomicsToolkit/cactus?tab=readme-ov-file | Physical Sciences | https://www.cactuscode.org/documentation/tutorials/index.html https://www.cactuscode.org/documentation/UsersGuide.pdf |
Anvil: https://www.rcac.purdue.edu/software/cactus | Anvil: 2.0.5, 2.2.1, 2.2.3-Gpu, 2.2.3, 2.4.0-Gpu, 2.4.0, 2.5.2-Gpu, 2.5.2, 2.6.5-Gpu, ... | Scientific Computing | |
cafe | Anvil | Cafe is a computational tool for the study of gene family evolution. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/cafe/cafe.html |
Cafe is a computational tool for analyzing gene family evolution. It implements a stochastic model to infer the birth-and-death process of gene family evolution. | Cafe allows users to estimate the birth (duplication) and death (deletion) rates of gene families, assess the significance of gene family size changes, and infer ancestral gene family sizes. It also provides visualizations of the results. | https://hahnlab.github.io/CAFE/manual.html | Bioinformatics Tool | Evolutionary Genomics | Genomics | Computational Biology, Bioinformatics | https://github.com/hahnlab/CAFE5 | Biological Sciences | https://github.com/hahnlab/CAFE5/blob/master/docs/tutorial/tutorial.md | Anvil: https://www.rcac.purdue.edu/software/cafe | Anvil: 4.2.1, 5.0.0 | Statistical Analysis | |
cairo | Aces, Faster | Cairo is a 2D graphics library with support for multiple output devices. Currently supported output targets include the X Window System (via both Xlib and XCB), Quartz, Win32, image buffers, PostScript, PDF, and SVG file output. Description Source: https://cairographics.org/ |
Cairo is a 2D graphics library with support for multiple output devices. It provides a vector-based rendering engine for high-quality graphics with full support for transparency and anti-aliasing. | Cairo supports various output targets including image buffers, PNG files, PDF files, SVG files, PostScript files, and direct rendering to X Window System and Windows surfaces. It offers a simple API for drawing paths, text, and images with advanced features like gradients, patterns, and transformations. | https://www.cairographics.org/manual/ | Library | Computer Science | Graphics | Graphics Library, 2D Graphics, Rendering Engine | https://cairographics.org/ | Computer & Information Sciences | https://www.cairographics.org/tutorial/ https://zetcode.com/gfx/cairo/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.16.0, 1.17.4, 1.17.8 Faster: 1.16.0, 1.17.4, 1.17.8 |
Graphics Library | |
canu | Anvil, Faster | Canu is a fork of the Celera Assembler, designed for high-noise single-molecule sequencing (such as the PacBio RS II/Sequel or Oxford Nanopore MinION). Description Source: https://github.com/marbl/canu |
Canu is a software tool that is used for assembling genomes using nanopore sequencing data. It is designed to be efficient and scalable, making it suitable for large and complex genomes. | Some of the key features of Canu include error correction, trimming, assembling, and visualization of long-read sequencing data. It also includes support for multi-genome assembly and variant calling. | https://canu.readthedocs.io/en/latest/ | Bioinformatics Tool | Genome Assembly, Long-Read Sequencing | Genomics, Bioinformatics | Genome Assembly, Nanopore Sequencing, Long-Read Sequencing, Bioinformatics | https://github.com/marbl/canu | Biological Sciences | https://canu.readthedocs.io/en/latest/quick-start.html https://canu.readthedocs.io/en/latest/tutorial.html |
Anvil: https://www.rcac.purdue.edu/software/canu Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 2.1.1, 2.2 Faster: 2.2 |
Genome Assembler | |
capstone | Aces, Faster | Capstone is a lightweight multi-platform, multi-architecture disassembly framework. Description Source: https://www.capstone-engine.org/ |
Capstone is a disassembly framework with the target of becoming the ultimate disasm engine for binary analysis and reversing in the security community. Created by Nguyen Anh Quynh, it is open-source software distributed under the Simplified BSD License. | Capstone supports multiple hardware architectures and provides a rich set of APIs for disassembling machine code, including instruction semantics, details, and operand access. It is designed to be lightweight and efficient, making it suitable for various applications such as static code analysis, dynamic binary instrumentation, malware analysis, and more. | https://www.capstone-engine.org/documentation.html | Tool | Cybersecurity | Computer Science | Disassembly, Binary Analysis, Reverse Engineering | https://www.capstone-engine.org/ | Computer & Information Sciences | https://www.capstone-engine.org/documentation.html#programming | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.0.1 Faster: 5.0.1 |
Disassembly Framework | |
captum | Aces | Captum (“comprehension” in Latin) is an open source, extensible library for model interpretability built on PyTorch. Captum helps ML researchers more easily implement interpretability algorithms that can interact with PyTorch models. It also allows researchers to quickly benchmark their work against other existing algorithms available in the library. Description Source: https://captum.ai/docs/introduction.html |
Captum is an extensible library for model interpretation in PyTorch. It provides a flexible and unified API for different interpretability methods and allows users to easily interpret deep learning models. | 1. Support for various interpretability algorithms such as Integrated Gradients, Feature Ablation, Occlusion, DeepLift, etc. 2. Compatibility with PyTorch for seamless integration into PyTorch-based deep learning workflows. 3. Extensibility to create custom interpretation algorithms or extend existing ones. 4. Visualization tools to aid in the interpretation of model decisions. 5. Facilitates understanding of model behavior and decisions for better model debugging and trustworthiness. | https://captum.ai/docs/introduction | Model Interpretation | Computer Science | Artificial Intelligence, Machine Learning | Interpretability, Model Interpretation, Deep Learning, Pytorch | https://captum.ai/ | Computer & Information Sciences | https://captum.ai/tutorials/ | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.5.0 | Interpretability Library | |
cartopy | Aces, Faster | Cartopy is a Python package designed to make drawing maps for data analysis and visualisation easy. Description Source: https://github.com/SciTools/cartopy |
Cartopy is a Python package designed for geospatial data processing to produce high-quality visualizations of maps using matplotlib. It aims to simplify and enhance the mapping capabilities in Python, providing rich, interactive, and customized maps for various scientific disciplines. | Supports Various Map Projections & Coordinate Reference Systems, Integration With Matplotlib For Plotting Spatial Data, Ability To Plot Data On Maps, Add Coastlines, Borders, & Gridlines, Provides Tools For Geospatial Data Manipulation & Analysis | https://scitools.org.uk/cartopy/docs/latest/ | Python Library | Geophysics & Geochemistry | Earth & Environmental Sciences | Geospatial Data Processing, Data Visualization, Python Library, Mapping, Scientific Visualization | https://github.com/SciTools/cartopy | Physical Sciences | https://github.com/SciTools/cartopy/tree/main/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.20.3, 0.22.0 Faster: 0.20.0, 0.20.3, 0.22.0 |
Visualization Tool | |
catch2 | Aces, Faster | Catch2 is mainly a unit testing framework for C++, but it also provides basic micro-benchmarking features, and simple BDD macros. Description Source: https://github.com/catchorg/Catch2/tree/devel?tab=readme-ov-file |
Catch2 is a C++ testing framework that is easy to use, yet powerful. It supports test-driven development, behavior-driven development, and specification by example. | 1. Lightweight and easy to get started with\r 2. Support for TDD, BDD, and specification by example\r 3. Extensive set of matchers to write expressive and flexible test specifications\r 4. Ability to define test cases with minimal boilerplate code\r 5. Rich command-line interface for executing tests and generating reports |
https://github.com/catchorg/Catch2/blob/devel/docs/Readme.md | Testing Framework | Software Engineering, Systems, & Development | Computer Science | Testing Framework, C++, Unit Testing | https://github.com/catchorg/Catch2 | Engineering & Technology | https://github.com/catchorg/Catch2/blob/devel/docs/tutorial.md#top | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.4.0 Faster: 2.13.9, 3.4.0 |
Developer Tools | |
ccache | Aces, Faster | Ccache is a compiler cache. It speeds up recompilation by caching previous compilations and detecting when the same compilation is being done again. Description Source: https://ccache.dev/ |
ccache is a compiler cache tool designed to speed up C and C++ compilation by caching previous compilations. It acts as a caching proxy for compilers, storing compiled object files in a cache directory, which can be reused when the same compilation is done again. This reduces compilation times significantly, especially during iterative development processes. | Caching Compiled Object Files For Faster Compilation Times, Transparently Intercepting Compiler Calls, Support For Various Compilers & Build Systems, Customizable Cache Size & Behavior, Tracking Dependencies To Invalidate Outdated Cache Entries | https://linux.die.net/man/1/ccache | Compiler Utility | General | General | Compiler Cache, C/C++ Compilation, Build Optimization | https://ccache.dev/ | Engineering & Technology | https://ccache.dev/manual/latest.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.6.1, 4.6.3 Faster: 4.6.1 |
Development Tools | |
ccdb | Delta | CCDB: Cray's comparative debugger features a graphical user interface and extends the comparative debugging capabilities of lgdb, allowing users to easily compare data structures between two executing applications. Description Source: https://support.hpe.com/hpesc/public/docDisplay?docId=a00113984en_us&page=Cray_Debugger_Support_Tools.html |
CCDB (Cell Cycle Database) is a freely accessible, comprehensive resource for the cell cycle community. It provides information and tools to study cell cycle regulation and its role in cancer and other diseases. | Access To Curated Cell Cycle-Related Data, Tools For Analyzing Cell Cycle Regulation, Links To Relevant Literature & Resources | https://cpe.ext.hpe.com/docs/debugging-tools/cpedocs_ccdb/guide/index.html | Curated Data Resource | Cell Cycle Regulation | Cell Biology | Cell Cycle, Cell Biology, Database | https://cpe.ext.hpe.com/docs/debugging-tools/cpedocs_ccdb/cpedocs_index_chunk.html | Biological Sciences | https://support.hpe.com/hpesc/public/docDisplay?docId=a00113984en_us&page=Using_CCDB.html&docLocale=en_US | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Database | ||
cce | Delta | Compiler Construction Engine (CCE) is a software tool used for building compilers and interpreters. It provides a set of tools and libraries to assist in the creation of programming language implementations. | 1. Lexical analysis and parsing tools\r 2. Abstract Syntax Tree (AST) generation\r 3. Code generation and optimization capabilities\r 4. Integrated development environment for language design and compiler construction\r 5. Support for various programming languages and target architectures |
Compiler/Interpreter | Software Engineering | Computer Science | Compiler, Interpreter, Programming Language, Compiler Construction | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 16.0.1 | Development Tools | |||||
cce-mixed | Delta | cce-mixed is a software package designed for performing calculations in the framework of many-body perturbation theory for the electronic structure of solids. It focuses on the GW approximation, self-energy calculations, and the solution of the Bethe-Salpeter equation for optical excitations. | 1. GW approximation calculations for electronic structure analysis\r 2. Self-energy calculations\r 3. Bethe-Salpeter equation solutions for optical excitations\r 4. Solid-state materials electronic structure analysis |
Electronic Structure Calculation | Electronic Structure Of Solids | Condensed Matter Physics | Computational Chemistry, Quantum Mechanics, Electronic Structure Calculations | Physical Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 16.0.1 | Computational Software | |||||
ccl | Kyric | CCL (Cpp Command Line Library) is a C++ library targeting Unix platform that makes it easy to define and parse command line arguments. It provides a simple and intuitive way to define and parse command-line arguments for C++ programs. | 1. Easy definition of command line arguments with strong typing. 2. Automatic generation of help messages. 3. Support for positional arguments, switches, and flags. 4. No external dependencies. | https://ccl.clozure.com/docs/ccl.html | Command Line Interface, C++ Library | https://ccl.clozure.com/ | https://ccl.clozure.com/docs/ccl.html#using-clozure-cl | Kyric: Latest, 2021.1.1 | ||||||||
ccs | Anvil | Pbccs is a tool to generate Highly Accurate Single-Molecule Consensus Reads (HiFi Reads). | The Consensus Computational Suite (CCS) is a collection of open-source tools and algorithms for analyzing, visualizing, and interpreting data in the context of consensus algorithms. It includes various modules for sequence assembly, genome scaffolding, variant calling, and haplotype phasing. | Sequence Assembly, Genome Scaffolding, Variant Calling, Haplotype Phasing | Bioinformatics Tool | Bioinformatics, Computational Biology, Sequence Analysis, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/ccs | Anvil: 6.4.0 | Computational Software | ||||||
cd-hit | Aces, Anvil, Faster | Cd-hit is a very widely used program for clustering and comparing protein or nucleotide sequences. | cd-hit is a widely used program for clustering and comparing protein or nucleotide sequences. It clusters a large set of sequences to reduce redundancy and generate a non-redundant representative set. This tool is beneficial for sequence analysis, especially in bioinformatics studies. | 1. Clustering of protein or nucleotide sequences\r 2. Reducing redundancy in large sequence datasets\r 3. Generating non-redundant representative sequences\r 4. Alignment-based and word-counting algorithms\r 5. Various clustering and similarity threshold options |
Bioinformatics Software | Sequence Analysis | Bioinformatics | Sequence Analysis, Clustering, Bioinformatics | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/cd-hit Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.8.1 Anvil: 4.8.1 Faster: 4.8.1 |
Clustering Tool | ||||
cdat | Faster | The Climate Data Analysis Tools (CDAT) is an open-source software package that provides capabilities for accessing, analyzing, and visualizing climate and weather data. CDAT is designed to help researchers in the atmospheric and climate sciences analyze large datasets and perform complex data tasks. | Accessing Climate & Weather Data, Analyzing Large Datasets, Visualizing Data, Performing Complex Data Tasks | Tool | Climate & Global Dynamics | Atmospheric Sciences | Climate Data, Weather Data, Data Analysis, Data Visualization | Earth & Environmental Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 8.2.1-Python-3.8.2 | Data Analysis & Visualization | |||||
cdbtools | Anvil | Cdbtools is a collection of tools used for creating indices for quick retrieval of any particular sequences from large multi-FASTA files. | cdbtools is a set of command-line utilities for manipulating and working with Constant Database (CDB) files. These utilities provide functionality for creating, reading, updating, and deleting records in CDB files. | Key features of cdbtools include the ability to efficiently store and retrieve key-value pairs, support for fast lookups and searches within CDB files, and tools for managing and maintaining CDB databases. | Command-Line Utility | Cdb, Command-Line, Data Manipulation | Anvil: https://www.rcac.purdue.edu/software/cdbtools | Anvil: 0.99 | Database Management | |||||||
cdo | Aces, Anvil, Delta, Faster, Stampede3 | CDO is a collection of command line Operators to manipulate and analyse Climate and NWP model Data. Supported data formats are GRIB 1/2, netCDF 3/4, SERVICE, EXTRA and IEG. There are more than 600 operators available. Description Source: https://code.mpimet.mpg.de/projects/cdo |
Climate Data Operators (CDO) is a collection of command-line operators for manipulating and analyzing climate and numerical weather prediction (NWP) model data. | Supports A Wide Range Of File Formats Including Grib, Netcdf, Hdf, & More, Provides Tools For Data Selection, Slicing, Aggregation, Interpolation, Calculation, & Visualization, Enables Batch Processing & Scripting For Automatic Data Processing, Includes Comprehensive Documentation & Support For A Variety Of Operations On Climate Data | https://code.mpimet.mpg.de/projects/cdo/wiki/Cdo#Documentation | Command Line Tool | Climate Data, Data Manipulation, Command Line, Data Analysis | https://code.mpimet.mpg.de/projects/cdo | Earth & Environmental Sciences | https://code.mpimet.mpg.de/projects/cdo/wiki/Tutorial | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/cdo Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 2.0.5 Anvil: 1.9.9 Delta: 2.4.0 Faster: 1.9.10 Stampede-3: 2.3.0 |
Data Processing & Analysis | |||
cdsapi | Aces | The Climate Data Store (CDS) Application Program Interface (API) is a service providing programmatic access to CDS data. Description Source: https://cds.climate.copernicus.eu/api-how-to |
cdsapi is a Python client library for Climate Data Store (CDS) API, which allows users to access climate and weather data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). | 1. Access climate and weather data from ECMWF's CDS API. 2. Retrieve datasets for various parameters like temperature, precipitation, wind speed, etc. 3. Download data in multiple formats such as NetCDF and GRIB. 4. Simplified authentication process for accessing ECMWF data. 5. Efficient querying and downloading of meteorological data. | https://confluence.ecmwf.int/display/CKB/Climate+Data+Store+%28CDS%29+API+Keywords | Api | Climate/Weather | Python Library, Climate Data, Weather Data | https://github.com/ecmwf/cdsapi | Earth & Environmental Sciences | https://cds.climate.copernicus.eu/api-how-to | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.5.1 | Library | ||
cegma | Anvil | CEGMA (Core Eukaryotic Genes Mapping Approach) is a pipeline for building a set of high reliable set of gene annotations in virtually any eukaryotic genome. | CEGMA (Core Eukaryotic Genes Mapping Approach) is a pipeline for predicting core eukaryotic genes in genome assemblies. It is designed to identify a set of conserved genes that are expected to be present in all eukaryotic genomes. CEGMA is commonly used for evaluating the completeness and quality of genome assemblies. | Prediction Of Core Eukaryotic Genes, Assessment Of Genome Assembly Completeness, Identification Of Conserved Genes In Eukaryotic Genomes | Tool | Genome Assembly | Genomics | Genome Assembly, Core Eukaryotic Genes, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cegma | Anvil: 2.5 | Bioinformatics | ||||
cellbender | Anvil | Cellbender is a software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing (scRNA-seq) data. | CellBender is a Python package for processing, denoising, and removing technical variation from single-cell RNA-seq data. It offers methods for the removal of ambient RNA contamination, batch effects, and other technical artifacts commonly found in single-cell RNA-seq datasets. | Denoising Single-Cell RNA-Seq Data, Removing Ambient RNA Contamination, Correcting Batch Effects, Addressing Technical Artifacts In Scrna-Seq Datasets | Python Library | Single-Cell RNA-Seq Data Analysis | Genetics | Single-Cell RNA-Seq, Data Processing, Denoising, Batch Effects, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellbender | Anvil: 0.2.0, 0.2.2 | Data Processing | ||||
cellchat | Anvil | CellChat: Inference and analysis of cell-cell communication. Description Source: https://purduercac-applications.readthedocs.io/en/latest/Biocontainers/r-cellchat/r-cellchat.html |
CellChat is a Python package designed for cell-cell communication analysis in single-cell RNA-seq data. It provides a comprehensive toolkit for studying ligand-receptor interactions and signaling networks between different cell types within complex tissues. | Identification & Visualization Of Ligand-Receptor Interactions, Inference Of Signaling Networks Between Cell Types, Integration Of Scrna-Seq Data To Study Intercellular Communication, Visualization Of Communication Networks & Pathways | Python Library | Single-Cell Analysis | Cell Biology | Single-Cell RNA Sequencing, Cell-Cell Communication, Bioinformatics, Python Package | https://github.com/sqjin/CellChat | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellchat | Bioinformatics Tool | ||||
cellphonedb | Anvil | CellPhoneDB is a publicly available repository of curated receptors, ligands and their interactions. | CellPhoneDB is a publicly available repository of curated receptors, ligands, and interactions between immune and stromal cells. | 1. Curated database of receptors, ligands, and interactions in immune and stromal cells. 2. Provides information on cell-cell communication in biological systems. 3. Enables the analysis of ligand-receptor interactions and signaling networks. 4. Facilitates the study of cell communication in the context of complex tissues and organs. | Computational Software | Bioinformatics, Hpc Tools | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellphonedb | Anvil: 2.1.7 | Bioinformatics | ||||||
cellranger | Anvil | A set of analysis pipelines that perform sample demultiplexing, barcode processing, single cell 3' and 5' gene counting, V(D)J transcript sequence assembly and annotation, and Feature Barcode analysis from single cell data. Description Source: https://www.10xgenomics.com/support/software/cell-ranger/latest |
Cell Ranger is a set of analysis pipelines that process Chromium Single Cell 3’ RNA-seq data. It includes software for demultiplexing, mapping, filtering, and counting single-cell RNA-Seq data. | Demultiplexing, mapping, filtering, counting single-cell RNA-Seq data. | https://www.10xgenomics.com/support/software/cell-ranger/latest/resources/cr-command-line-arguments | Sciences | Biology | Bioinformatics, Single-Cell RNA-Seq, Data Analysis | https://www.10xgenomics.com/support/software/cell-ranger/latest | Biological Sciences | https://www.10xgenomics.com/support/software/cell-ranger/latest/tutorials | Anvil: https://www.rcac.purdue.edu/software/cellranger | Anvil: 6.0.1, 6.1.1, 6.1.2, 7.0.0, 7.0.1, 7.1.0 | Bioinformatics | ||
cellranger-arc | Anvil | Cell Ranger ARC is a set of analysis pipelines that process Chromium Single Cell Multiome ATAC + Gene Expression sequencing data to generate a variety of analyses pertaining to gene expression (GEX), chromatin accessibility, and their linkage. | Cell Ranger ARC is a software package for analyzing single-cell chromatin accessibility data. It identifies accessible chromatin regions (peaks), cluster cells based on similarity of peak accessibility, and performs differential accessibility analysis across clusters. | Identification Of Accessible Chromatin Regions (Peaks), Clustering Of Cells Based On Peak Accessibility, Differential Accessibility Analysis Across Clusters | Bioinformatics Tool | Genetics | Bioinformatics | Single-Cell Analysis, Chromatin Accessibility, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellranger-arc | Anvil: 2.0.2 | Data Analysis Tool | ||||
cellranger-atac | Anvil | Cell Ranger ATAC is a software application for analyzing and visualizing Single Cell ATAC data produced by the 10x Genomics Chromium platform. Software Description=https://support.10xgenomics.com/single-cell-atac/software/overview/welcome | https://www.10xgenomics.com/support/single-cell-atac/documentation | Application | Sciences | Biology | https://support.10xgenomics.com/single-cell-atac/software/overview/welcome | https://pages.10xgenomics.com/sup-how-to-single-cell-atac-v2.html | Anvil: https://www.rcac.purdue.edu/software/cellranger-atac | Anvil: 2.0.0, 2.1.0 | Bioinformatics | |||||
cellranger-dna | Anvil | Cell Ranger DNA is a software package from 10x Genomics that enables the analysis of single-cell DNA sequencing data. It is specifically designed to process single-cell data from linked-read sequencing technologies, such as the 10x Genomics Chromium platform, to identify structural variants, copy number variations, and clonality in individual cells. | Analysis Of Single-Cell DNA Sequencing Data, Identification Of Structural Variants, Detection Of Copy Number Variations, Estimation Of Clonality In Individual Cells, Support For Linked-Read Sequencing Technologies | Tool | Genomics | Genetics | Single-Cell DNA Sequencing, Structural Variants, Copy Number Variations, Clonality Analysis, Linked-Read Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellranger-dna | Anvil: 1.1.0 | Bioinformatics | |||||
cellrank | Anvil | Cellrank is a toolkit to uncover cellular dynamics based on Markov state modeling of single-cell data. | CellRank is a Python library for identifying cell transitions and their drivers in single-cell RNA sequencing data. It provides a comprehensive framework for modeling cell fate decisions using RNA velocity, transition matrices, and attractor inference. | Cell Fate Decision Modeling, Identification Of Cell Transitions, Driver Analysis Of Transitions, RNA Velocity Analysis, Transition Matrices, Attractor Inference | Python Library | Computational Biology | Bioinformatics | Single-Cell RNA Sequencing, Cell Fate Decisions, Cell Transitions, Transcriptional Dynamics, Python Library | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellrank | Anvil: 1.5.1 | Library | ||||
cellrank-krylov | Anvil | Cellrank-krylov is the cellrank package with extra libraries that are useful for large datasets. | cellrank-Krylov is a Python library designed to provide cell fate prediction and lineage analysis for single-cell RNA sequencing data using Krylov subspace methods. It offers tools for exploring cell differentiation trajectories and uncovering crucial cell states in the data. | Cell Fate Prediction, Lineage Analysis, Single-Cell RNA Sequencing Data Analysis, Cell Differentiation Trajectories, Identification Of Key Cell States | Python Library | Single-Cell Analysis, Lineage Analysis, RNA Sequencing, Cell Fate Prediction | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellrank-krylov | Anvil: 1.5.1 | Computational Software | ||||||
cellsnp-lite | Anvil | cellSNP aims to pileup the expressed alleles in single-cell or bulk RNA-seq data, which can be directly used for donor deconvolution in multiplexed single-cell RNA-seq data, particularly with vireo, which assigns cells to donors and detects doublets, even without genotyping reference. | Cellsnp-lite is a variant calling tool for single-cell RNA sequencing data, specifically designed for genotyping and haplotype inference for diploid cells. It allows for accurately detecting single-nucleotide variations, small insertions and deletions, and single-cell genotyping from scRNA-seq data. | 1. Genotyping of single cells\r 2. Haplotype inference for diploid cells\r 3. Detection of single-nucleotide variations (SNVs) and small indels\r 4. Single-cell RNA sequencing data analysis\r 5. High accuracy in variant calling |
Variant Calling Tool | Single-Cell Genomics | Cell Biology | Variant Calling, Single-Cell RNA Sequencing, Genotyping, Haplotype Inference | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cellsnp-lite | Anvil: 1.2.2 | Bioinformatics Tool | ||||
celltypist | Anvil | Celltypist is a tool for semi-automatic cell type annotation. | CellTypist is a computational framework for unbiased cell type classification of single-cell RNA sequencing data. It integrates marker gene detection, cell type identification, and cluster-based classification to provide accurate and interpretable cell type annotations. | Marker Gene Detection, Cell Type Identification, Cluster-Based Classification, Unbiased Classification | Bioinformatics Tool | Single-Cell Omics | Bioinformatics | Single-Cell RNA Sequencing, Cell Type Classification, Computational Framework | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/celltypist | Anvil: 0.2.0, 1.1.0 | Analysis Tool | ||||
centrifuge | Anvil | Centrifuge is a novel microbial classification engine that enables rapid, accurate, and sensitive labeling of reads and quantification of species on desktop computers. | Centrifuge is a tool used for rapid and sensitive classification of metagenomic sequencing data. It utilizes a Burrows-Wheeler transform (BWT) and FM-index for rapid and memory-efficient classification of reads against a comprehensive and up-to-date protein sequence database. | Classification Of Metagenomic Sequencing Data, Utilizes Burrows-Wheeler Transform (Bwt) & Fm-Index, Rapid & Memory-Efficient, Uses A Comprehensive Protein Sequence Database | Analysis Tool | Metagenomics | Microbiology | Bioinformatics, Metagenomics, Sequencing Data Analysis, Microbiome Analysis, Computational Biology | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/centrifuge | Anvil: 1.0.4_Beta | Bioinformatics Tool | ||||
cereal | Expanse | cereal is a header-only C++11 serialization library. cereal takes arbitrary data types and reversibly turns them into different representations, such as compact binary encodings, XML, or JSON. | Cereal is a C++11 library for serialization. It is designed to be fast, compact, and have an easy-to-use API. | Cereal provides functionalities for serializing and deserializing data structures in C++. It supports a wide range of data types, including custom classes, and offers flexibility in serialization formats. | Data Serialization | Serialization, C++, Library | Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 1.3.0 | Library | ||||||
cesm | Faster | The Community Earth System Model is a fully coupled global climate model developed in collaboration with colleagues in the research community. CESM provides state of the art computer simulations of Earth's past, present, and future climate states. Description Source: https://www.cesm.ucar.edu/ |
The Community Earth System Model (CESM) is a fully-coupled, global climate model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. | Fully-Coupled Climate Model, Global Climate Simulations, Multi-Component Model, Advanced Earth System Modeling Capabilities | https://escomp.github.io/CESM/versions/cesm2.2/html/introduction.html | Computational Software | Climate & Global Dynamics | Earth & Environmental Sciences | Climate Modeling, Earth System Modeling, Global Climate Simulations | https://www.cesm.ucar.edu/models/cesm2 | Earth & Environmental Sciences | https://www.youtube.com/playlist?list=PLsqhY3nFckOEX41g8ZUnhGT2c--5kUZ1V | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.1.3 | Modeling & Simulation | |
cesm-deps | Aces, Faster | The Community Earth System Model is a fully coupled global climate model developed in collaboration with colleagues in the research community. CESM provides state of the art computer simulations of Earth's past, present, and future climate states. Description Source: https://www.cesm.ucar.edu/ |
CESM-DEPS is a set of dependencies and tools for supporting the Community Earth System Model (CESM) software. It includes various libraries, compilers, and software packages necessary for running CESM simulations. | Provides Essential Dependencies & Tools For Cesm Software, Includes Libraries, Compilers, & Other Software Required For Cesm Simulations, Ensures Smooth Operation & Performance Optimization Of Cesm Models | https://escomp.github.io/CESM/versions/cesm2.2/html/introduction.html | Libraries & Dependencies | Sciences | Dependencies, Cesm, Earth System Model, Simulation, Software Package | https://www.cesm.ucar.edu/models/cesm2 | Earth & Environmental Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2 Faster: 2 |
Tools & Utilities | |||
cffi | Aces, Faster | C Foreign Function Interface for Python. Interact with almost any C code from Python, based on C-like declarations that you can often copy-paste from header files or documentation. | CFFI is a Foreign Function Interface between Python and C. It allows calling C code from Python and using Python code from C. It provides a way to interact with foreign functions and call them from Python without having to write any C code. | Easily Call C Functions From Python, Efficiently Share Data Between C & Python, No Need To Write C Code With The Use Of Cffi Apis | Interfacing | Foreign Function Interface, C Library Integration, Python | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.15.1 Faster: 1.15.1 |
Library | ||||||
cfitsio | Aces, Faster | CFITSIO is a library of C and Fortran subroutines for reading and writing data files in FITS (Flexible Image Transport System) data format. CFITSIO provides simple high-level routines for reading and writing FITS files that insulate the programmer from the internal complexities of the FITS format. Description Source: https://heasarc.gsfc.nasa.gov/fitsio/ |
CFITSIO is a library of C and Fortran subroutines for reading and writing data files in FITS (Flexible Image Transport System) data format. | CFITSIO provides a comprehensive set of interfaces for reading, writing, and manipulating FITS files. It supports various data types, compression methods, and image formats commonly used in astronomical and scientific data. | https://heasarc.gsfc.nasa.gov/fitsio/c/c_user/cfitsio.html | Data Processing | Astronomy | Astronomy & Planetary Sciences | Astronomy, Data Processing, File Format, Fits | https://heasarc.gsfc.nasa.gov/fitsio/ | Physical Sciences | https://heasarc.gsfc.nasa.gov/docs/software/fitsio/quick/node2.html https://fits.gsfc.nasa.gov/fits_libraries.html#c_cfitsio https://heasarc.gsfc.nasa.gov/docs/software/fitsio/cexamples.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.2.0, 4.3.0 Faster: 3.49, 4.2.0, 4.3.0 |
Library | |
cfsan-snp-pipeline | Anvil | The CFSAN SNP Pipeline is a Python-based system for the production of SNP matrices from sequence data used in the phylogenetic analysis of pathogenic organisms sequenced from samples of interest to food safety. | The cfsan-snp-pipeline is a bioinformatics tool developed by the Center for Food Safety and Applied Nutrition (CFSAN) that is used for identifying single nucleotide polymorphisms (SNPs) from raw sequence data of bacterial genomes. | 1. Identification of single nucleotide polymorphisms (SNPs) in bacterial genomes.\r 2. Processing of raw sequence data from next-generation sequencing (NGS) platforms.\r 3. Phylogenetic analysis and comparison of bacterial strains based on SNP variations.\r 4. Visualization tools for SNP analysis results.\r 5. Integration with other bioinformatics tools and databases for additional analysis. |
Pipeline | Bioinformatics, Computational Biology, Sequence Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cfsan-snp-pipeline | Anvil: 2.2.1 | Bioinformatics Tool | ||||||
cgal | Aces, Expanse, Faster | CGAL is an open source software project that provides easy access to efficient and reliable geometric algorithms in the form of a C++ library. CGAL is used in various areas needing geometric computation, such as geographic information systems, computer aided design, molecular biology, medical imaging, computer graphics, and robotics. Description Source: https://www.cgal.org/ |
CGAL (Computational Geometry Algorithms Library) is a software library that provides a wide range of efficient and reliable geometric algorithms for use in various applications in computational geometry, such as mesh generation, geometric processing, visualization, and more. It is designed to be versatile, easy to use, and highly efficient. | 1. Robust and efficient algorithms for computational geometry\r 2. Support for a wide range of geometric data structures\r 3. Implementation of various geometric algorithms, such as convex hulls, triangulations, Voronoi diagrams, and more\r 4. Integration with other libraries and software tools\r 5. Extensive documentation and user support\r 6. Portable and compatible with multiple platforms |
https://doc.cgal.org/latest/Manual/dev_manual.html | Algorithm Library | Computational Geometry | Computer Science | Computational Geometry, Geometric Algorithms, Software Library | https://www.cgal.org/ | Computer & Information Sciences | https://doc.cgal.org/latest/Manual/tutorials.html | Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.14.3, 5.6 Expanse: Axpdrof, Jrg6Ven, Lnidf3A Faster: 4.14.3-Python-3.8.2, 4.14.3, 5.2 |
Library | |
cgns | Aces | The CFD General Notation System (CGNS) provides a standard for recording and recovering computer data associated with the numerical solution of the equations of fluid dynamics. It is designed to facilitate the exchange of data between sites and applications, as well as to help stabilize the archiving of fluid dynamics data. | 1. Supports the hierarchical structure of CFD computations.\r 2. Allows data to be written to a file so that it is portable across different machines and operating systems.\r 3. Provides mechanisms for modifying data as technologies advance, ensuring long-term viability of CFD data.\r 4. Offers a range of tools and conventions to support data interoperability. |
File Format | Fluid Dynamics | Fluid & Plasma Physics | Computational Software | Physical Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 4.4.0 | Data Exchange | |||||
chameleon | Aces | Chameleon is a framework written in C which provides routines to solve dense general systems of linear equations, symmetric positive definite systems of linear equations and linear least squares problems, using LU, Cholesky, QR and LQ factorizations. | Chameleon is a Python library for creating customizable color palettes for data visualization purposes. It provides a user-friendly interface to easily generate aesthetically pleasing color schemes for various types of visualizations. | 1. Generate custom color palettes\r 2. Easily customize color schemes\r 3. Compatibility with popular data visualization libraries\r 4. Seamless integration with Python data analysis workflows |
Library | Python Library, Data Visualization, Color Palette, Visualization, Python | Other Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.2.0 | Data Visualization Library | ||||||
chapel | Faster, Ookami | Chapel is a programming language designed for productive parallel computing at scale. Description Source: https://chapel-lang.org/ |
Chapel is an emerging parallel programming language developed by Cray Inc. specifically designed for productive high-performance computing (HPC). It is designed to improve the productivity of parallel programming and provide scalability and portability across various HPC platforms. | Supports A Multithreaded Execution Model With A Partitioned Global Address Space, Provides A High-Level & Expressive Syntax, Offers Support For Data Parallelism, Task Parallelism, & Nested Parallelism, Includes Features For Interoperability With Existing Languages Such As C, C++, & Fortran, Designed For Use In Large-Scale Parallel Computing Environments | https://chapel-lang.org/docs/ | Compiler | Parallel Programming, Hpc, High-Performance Computing, Programming Language | https://chapel-lang.org/ | Computer & Information Sciences | https://chapel-lang.org/tutorials.html | Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Faster: 1.29.0-Mpi Ookami: 1.33.0 |
Programming Language | |||
charliecloud | Aces, Faster, Stampede3 | Charliecloud provides user-defined software stacks (UDSS) for high-performance computing (HPC) centers. Description Source: https://hpc.github.io/charliecloud/ |
Charliecloud is a software tool that provides user-defined software stacks in userspace with no privileged operations or daemons. It uses containers for software isolation and runs in user space, making it lightweight and secure. | Lightweight & Secure Container Tool, User-Defined Software Stacks, No Privileged Operations Or Daemons, Runs In User Space | https://hpc.github.io/charliecloud/ | Tool | Containerization, Software Development, Research Tools | https://github.com/hpc/charliecloud | Computer & Information Sciences | https://hpc.github.io/charliecloud/tutorial.html, | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 0.33 Faster: 0.31, 0.33 Stampede-3: 0.36 |
Containerization | |||
charm | Darwin | CHARM (Chemistry at Harvard Macromolecular Mechanics) is a molecular mechanics force field for the simulation of proteins, nucleic acids, carbohydrates, and lipids. It is widely used in the field of computational biology and bioinformatics for studying the structure, dynamics, and interactions of biomolecular systems. | 1. Simulation of proteins, nucleic acids, carbohydrates, and lipids\r 2. Calculation of molecular energies and forces\r 3. Modeling of biomolecular interactions\r 4. Analysis of molecular dynamics trajectories\r 5. Integration with various simulation packages |
Simulation Software | Computational Biology, Structural Biology | Bioinformatics, Biophysics | Molecular Mechanics, Biomolecular Simulation, Protein Structure Prediction | Biological Sciences | Molecular Mechanics Force Field | |||||||
charmpp | Expanse | Charm++ is a parallel programming framework in C++ supported by an adaptive runtime system, which enhances user productivity and allows programs to run portably from small multicore computers (your laptop) to the largest supercomputers. | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Ldvm3K4, Ukcmwdo, ... | ||||||||||||
check | Aces, Faster | Check is a unit testing framework for C. It features a simple interface for defining unit tests, putting little in the way of the developer. Tests are run in a separate address space, so both assertion failures and code errors that cause segmentation faults or other signals can be caught. Description Source: https://libcheck.github.io/check/ |
https://libcheck.github.io/check/doc/doxygen/html/check_8h.html | https://libcheck.github.io/check/ | https://libcheck.github.io/check/doc/check_html/check_3.html#Tutorial | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.15.2 Faster: 0.15.2 |
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checkm | Bridges-2 | CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. It provides robust estimates of genome completeness and contamination by using collocated sets of genes that are ubiquitous and single-copy within a phylogenetic lineage. Description Source: https://github.com/Ecogenomics/CheckM/wiki/Introduction#about |
CheckM is a software tool for assessing the quality of microbial genomes recovered from isolates, single cells, or metagenomes. It provides robust statistical evaluation of genome completeness and contamination, as well as identification of marker genes for phylogenetic placement. | Estimates Genome Completeness & Contamination, Identifies Marker Genes For Phylogenetic Analysis, Supports Analysis Of Microbial Genomes From Isolates, Single Cells, Or Metagenomes, Provides Detailed Reports & Visualizations | https://github.com/Ecogenomics/CheckM/wiki | Bioinformatics Tool | Microbial Ecology | Ecology | Microbial Genomics, Genome Quality Assessment, Phylogenetic Analysis, Bioinformatics | https://ecogenomics.github.io/CheckM/ | Biological Sciences | https://github.com/Ecogenomics/CheckM/wiki/Quick-Start | Bridges-2: https://www.psc.edu/resources/software/checkm | Bridges-2: 1.1.3 | Genomics Tool | |
checkm-genome | Anvil | Checkm-genome provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. | CheckM-Genome is a software tool used for assessing the quality of genomes derived from metagenome-assembled data. It provides insights into the completeness and contamination levels of bacterial and archaeal genomes, aiding in the evaluation of genome quality in microbial ecology and metagenomics studies. | Assessment Of Genome Completeness, Estimation Of Genome Contamination Levels, Identification Of Marker Genes & Lineage-Specific Marker Sets, Visualization Of Results & Quality Metrics | Genome Quality Assessment Tool | Microbial Ecology | Environmental Biology | Metagenomics, Microbial Ecology, Genome Quality Assessment | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/checkm-genome | Anvil: 1.2.0, 1.2.2 | Bioinformatics | ||||
chemprop | Aces | Chemprop is a message passing neural network for molecular property prediction. Description Source: https://chemprop.readthedocs.io/en/latest/ |
Chemprop is a deep learning-based tool for molecular property prediction. It allows users to train models to predict chemical properties and enables transfer learning to easily apply pre-trained models to new datasets. | Deep Learning-Based Molecular Property Prediction, Transfer Learning For Easy Application Of Pre-Trained Models, Flexible Model Architecture Customization | https://chemprop.readthedocs.io/en/latest/ | Bioinformatics | Chemoinformatics, Molecular Property Prediction, Deep Learning | https://github.com/chemprop/chemprop | Chemical Sciences | https://chemprop.readthedocs.io/en/latest/tutorial.html, | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.5.2-Cuda-11.7.0 | Machine Learning Tool | |||
chewbbaca | Anvil | chewBBACA is a comprehensive pipeline including a set of functions for the creation and validation of whole genome and core genome MultiLocus Sequence Typing (wg/cgMLST) schemas, providing an allele calling algorithm based on Blast Score Ratio that can be run in multiprocessor settings and a set of functions to visualize and validate allele variation in the loci. chewBBACA performs the schema creation and allele calls on complete or draft genomes resulting from de novo assemblers. | ChewBBACA (Chew Sequence-Based Typing Tool) is a suite of tools specifically designed for whole-genome sequence analysis, dedicated to the provision of high-resolution sequence-based microbial genotyping. | 1. Whole-genome sequence analysis\r 2. High-resolution microbial genotyping\r 3. Detection of core and accessory genome elements\r 4. Support for bacterial typing tasks\r 5. Analysis of large genomic datasets\r 6. Phylogenetic inference and visualization |
Tool | Microbial Genomics | Genomics | Whole-Genome Analysis, Microbial Genotyping, Bacterial Typing, Phylogenetic Inference, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/chewbbaca | Anvil: 2.8.5 | Bioinformatics | ||||
chimerax | Aces, Faster | UCSF ChimeraX is the next-generation visualization program from the Resource for Biocomputing, Visualization, and Informatics at UC San Francisco, following Chimera | ChimeraX is a software tool for the visualization and analysis of molecular structures, density maps, and related data. It is widely used in the field of structural biology and computational chemistry for studying complex biomolecular systems. | Interactive Visualization Of Molecular Structures & Density Maps, Molecular Modeling & Analysis Tools, Integration With Various Structural Biology Data Formats, Support For Virtual Reality Visualization, Scripting Capabilities For Automation & Customization | https://www.cgl.ucsf.edu/chimerax/docs/index.html | Analysis & Visualization Tool | Structural Biology | Bioinformatics | Molecular Visualization, Structural Biology, Computational Chemistry | https://www.cgl.ucsf.edu/chimerax/ | Biological Sciences | https://www.rbvi.ucsf.edu/chimerax/tutorials.html https://www.rbvi.ucsf.edu/chimerax/docs/videos/ https://rbvi.github.io/chimerax-recipes/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.3, 1.6.1, 1.7.1 Faster: 1.2.5, 1.4, 1.5, 1.6.1, 1.7 |
Molecular Visualization | |
chopper | Anvil | Chopper is Rust implementation of NanoFilt+NanoLyse, both originally written in Python. | Chopper is a tool designed for efficient removal of adapter sequences from high-throughput sequencing data. It helps in preprocessing raw sequencing reads by trimming adapter sequences to ensure high-quality downstream analysis. | Adapter Sequence Removal, Preprocessing Of Raw Sequencing Data, Quality Control, High-Throughput Sequencing Support | Bioinformatics Tool | Ngs Data Analysis | Bioinformatics | Bioinformatics, Ngs Data Analysis, Sequence Trimming, High-Throughput Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/chopper | Anvil: 0.2.0 | Sequence Analysis Tool | ||||
chromap | Anvil | Chromap is an ultrafast method for aligning and preprocessing high throughput chromatin profiles. | Chromap is a computational tool for comprehensive and integrative analysis of chromatin modifications from multiple ChIP-seq experiments. | Integrative Analysis Of Chromatin Modifications, Multi-Sample Chip-Seq Experiment Analysis, Statistical Analysis Of Chip-Seq Data, Visualization Of Chromatin Modification Patterns | Bioinformatics | Epigenetics | Genomics | Chromatin Modifications, Computational Biology, Bioinformatics, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/chromap | Anvil: 0.2.2 | Analysis Tool | ||||
cicero | Anvil | CICERO (Clipped-reads Extended for RNA Optimization) is an assembly-based algorithm to detect diverse classes of driver gene fusions from RNA-seq. | Cicero is a platform for automated text analysis and natural language processing. | Cicero provides tools for sentiment analysis, entity recognition, keyword extraction, text summarization, and language translation. It is designed to assist in extracting insights, trends, and patterns from large volumes of unstructured text data. | Text Analysis Tool | Text Analysis, Natural Language Processing | Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/cicero | Anvil: 1.8.1 | Computational Software | ||||||
cimfomfa | Aces | This library supports both MCL, a cluster algorithm for graphs, and zoem, a macro/DSL language. It supplies abstractions for memory management, I/O, associative arrays, strings, heaps, and a few other things. The string library has had heavy testing as part of zoem. | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 22.273 | ||||||||||||
circexplorer2 | Anvil | CIRCexplorer2 is a comprehensive and integrative circular RNA analysis toolset. It is the successor of CIRCexplorer with plenty of new features to facilitate circular RNA identification and characterization. | Circexplorer2 is a computational tool for identifying circular RNA (circRNA) from RNA-seq data. It supports the discovery, quantification, and visualization of circRNAs in a variety of biological samples. | 1. Detection of circular RNA events from RNA-seq data.\r 2. Quantification of circRNA expression levels.\r 3. Visualization of circRNA back-splicing junctions and expression profiles.\r 4. Differential expression analysis of circRNAs between conditions.\r 5. Integration with other analysis tools for comprehensive circRNA studies. |
Bioinformatics Tool | Transcriptomics | Molecular Biology | Circular RNA, RNA-Seq, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/circexplorer2 | Anvil: 2.3.8 | RNA Analysis Tool | ||||
circlator | Anvil | Circlator is a tool to circularize genome assemblies. | Circlator is a tool designed for circularizing and visualizing genome assemblies, specifically for circularizing genomes, fixing misassemblies, and improving the overall assembly quality. | Circularizing Genome Assemblies, Fixing Misassemblies, Improving Assembly Quality, Visualizing Genome Assemblies | Assembly Tools | Genome Assembly | Genomics | Genome Assembly, Bioinformatics, Genome Visualization, Assembly Improvement | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/circlator | Anvil: 1.5.5 | Genome Tools | ||||
circompara2 | Anvil | CirComPara2 is a computational pipeline to detect, quantify, and correlate expression of linear and circular RNAs from RNA-seq data that combines multiple circRNA-detection methods. | circompara2 is a tool for circular comparison of genomes. It allows for the visualization and comparison of genomic sequences in a circular representation, enabling the identification of similarities and differences between genomes. | Features of circompara2 include circular genome visualization, comparative genomics analysis, identification of genomic rearrangements, annotation comparison, and gene synteny analysis. | Tool | Comparative Genomics | Genomics | Genomics, Comparative Genomics, Genome Visualization, Gene Synteny | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/circompara2 | Anvil: 0.1.2.1 | Bioinformatics | ||||
circos | Anvil, Bridges-2 | Circos is a software package for visualizing data and information. It visualizes data in a circular layout — this makes Circos ideal for exploring relationships between objects or positions. Description Source: https://circos.ca/ |
Circos is a software package for visualizing data in a circular layout. It is widely used in genomics and other biological sciences to create visual representations of complex datasets. | Circular Layout Visualization, Highly Customizable Graphics, Support For Large Datasets, Integration Of Multiple Data Types, Publication-Quality Images | https://circos.ca/documentation/ | Visualization Tool | Genomics | Bioinformatics | Data Visualization, Genomics, Biological Sciences, Circular Layout | https://circos.ca/ | Biological Sciences | https://circos.ca/documentation/course/ https://circos.ca/tutorials/ https://circos.ca/documentation/images/small/ |
Anvil: https://www.rcac.purdue.edu/software/circos Bridges-2: https://www.psc.edu/resources/software/circos |
Anvil: 0.69.8 Bridges-2: 0.69-9 |
Data Visualization | |
ciri2 | Anvil | CIRI2: Circular RNA identification based on multiple seed matching | CIRI2 (CircRNA Identifier 2) is a comprehensive computational tool designed to efficiently and accurately identify circular RNAs (circRNAs) from high-throughput sequencing data. CircRNAs are a type of non-coding RNA with crucial functions in gene regulation and various biological processes. | 1. Detection of circRNAs: CIRI2 employs an algorithm that utilizes back-spliced reads to detect circRNAs within RNA-Seq data.\r 2. High accuracy: The tool integrates multiple strategies to enhance the accuracy of circRNA identification.\r 3. Multiple-file input: CIRI2 supports the analysis of multiple RNA-Seq samples simultaneously.\r 4. Visualization capabilities: Users can visualize the identified circRNAs and their characteristics through graphical outputs.\r 5. Customizable parameters: The tool offers flexibility in adjusting parameters based on user requirements. |
Analysis Tool | Molecular Biology | Genetics | Bioinformatics, Computational Biology, RNA-Seq, Circular RNA | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/ciri2 | Anvil: 2.0.6 | Bioinformatics Tool | ||||
ciriquant | Anvil | Ciriquant is a comprehensive analysis pipeline for circRNA detection and quantification in RNA-Seq data. | ciriquant is a computational software package for analyzing circadian oscillations in time-course data. It allows for the identification of significantly rhythmic genes and estimation of circadian parameters. | 1. Detection of circadian rhythms in time-course gene expression data. 2. Estimation of circadian parameters such as period and phase. 3. Statistical analysis to determine significantly rhythmic genes. 4. Visualization tools for circadian patterns. | Computational Biology, Time-Series Analysis, Biological Rhythms | Anvil: https://www.rcac.purdue.edu/software/ciriquant | Anvil: 1.1.2 | |||||||||
cistem | Aces, Faster | cisTEM is user-friendly software to process cryo-EM images of macromolecular complexes and obtain high-resolution 3D reconstructions from them. Description Source: https://cistem.org/ |
CISTEM is a computational framework designed for the prediction of dual phase RNA secondary structures. | CISTEM uses a double-layered classification system that combines features from primary sequence and secondary structure contexts to predict accurate RNA secondary structures. | https://cistem.org/documentation | Bioinformatics Tool | Computational Biology | Bioinformatics | Computational Framework, RNA Secondary Structures Prediction | https://cistem.org/ | Biological Sciences | https://cistem.org/sites/default/files/uploads/cisTEM_tutorial.pdf | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.0.0-Beta-Linux64 Faster: 1.0.0-Beta |
Prediction Software | |
ckdmip | Aces | Software for the Correlated K-Distribution Model Intercomparison Project (CKDMIP). | CKDmip is a software for computing cosmic microwave background (CMB) radiation temperature anisotropies and polarization spectra using the Cosmic Microwave Background (CMB) perturbation code. | CKDmip allows for the calculation of Cl's due to cosmic microwave background using CMB perturbation code, facilitating research and analysis in cosmology. | Hpc Tool | Cosmology | Astronomy & Planetary Sciences | Cosmic Microwave Background, Cmb Radiation, Temperature Anisotropies, Polarization Spectra | Physical Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.0 | Computational Software | ||||
clair3 | Anvil | Clair3 is a germline small variant caller for long-reads. | Clair3 is a variant caller for Illumina deep sequencing data. It is designed to detect germline and somatic variants in a flexible, scalable, and efficient manner. | Variant Calling For Illumina Deep Sequencing Data, Detection Of Germline & Somatic Variants, Scalable & Efficient Performance | Variant Caller | Variant Calling, Illumina, Sequencing Data | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/clair3 | Anvil: 0.1-R11, 0.1-R12 | Genomic Analysis Tool | ||||||
clairvoyante | Anvil | Clairvoyante is a deep neural network based variant caller. | clairvoyante is a deep learning-based tool for the prediction of variant calling accuracy. | It utilizes a deep neural network model for variant calling and can accurately predict the accuracy of variant calls made by different variant calling tools. The software identifies mislabeled pronouns and suffixes, improving the accuracy of variant prediction. | Command Line Tool | Bioinformatics | Genetics | Variant Calling, Deep Learning, Accuracy Prediction | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/clairvoyante | Anvil: 1.02 | Data Analysis | ||||
clang | Aces, Faster | The Clang project provides a language front-end and tooling infrastructure (its a compier) for languages in the C language family (C, C++, Objective C/C++, OpenCL, CUDA, and RenderScript) for the LLVM project. Description Source: https://clang.llvm.org/ |
Clang is a compiler front end for the C, C++, and Objective-C programming languages. It uses LLVM as its back end, providing highly optimized code generation. Clang is designed to provide fast compiles, expressive diagnostics, and a modular architecture for easy integration with other tools and libraries. | Support For C, C++, & Objective-C Languages, Highly Optimized Code Generation Using Llvm Back End, Fast Compilation Times, Expressive Diagnostics For Easy Debugging, Modular Architecture For Easy Integration With Other Tools & Libraries | https://clang.llvm.org/doxygen/index.html | Development Tool | Programming Languages & Compilers | Software Engineering, Systems, & Development | Compiler, Software Development, Programming Languages | https://clang.llvm.org/ | Computer & Information Sciences | https://clang.llvm.org/docs/UsersManual.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 13.0.1, 15.0.5, 16.0.6 Faster: 11.0.1, 12.0.1, 13.0.1-Cuda-11.4.1, 13.0.1, 16.0.6 |
Compiler | |
clang-aomp | Faster | clang-aomp is a compiler based on Clang that integrates the AMD Optimizing Compiler (AOCC) and OpenMP runtime. It is designed for accelerating applications on AMD GPUs. | Integration Of Amd Optimizing Compiler, Openmp Support, Optimizations For Amd Gpus | Compiler | Compiler, Openmp, Gpu Acceleration | Engineering & Technology | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 4.5.0 | Development Tools | |||||||
clck | Kyric | https://www.intel.com/content/www/us/en/developer/tools/oneapi/cluster-checker-documentation.html | https://www.intel.com/content/www/us/en/developer/tools/oneapi/cluster-checker.html#gs.5j2g84 | https://www.intel.com/content/www/us/en/docs/cluster-checker/user-guide/2021-7-2/getting-started.html | Kyric: Latest, 2021.1.1 | |||||||||||
clearcnv | Anvil | ClearCNV: CNV calling from NGS panel data in the presence of ambiguity and noise. | ClearCNV is a software tool designed for accurate copy number variation (CNV) detection from whole-exome sequencing (WES) data. It employs a Bayesian model-based approach to identify CNVs with high sensitivity and specificity. | Copy Number Variation (Cnv) Detection, Whole-Exome Sequencing (Wes) Data Analysis, Bayesian Model-Based Approach, High Sensitivity & Specificity | Bioinformatics Tool | Genomic Variations | Genomics | Cnv Detection, Genomic Analysis, Sequencing Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/clearcnv | Anvil: 0.306 | Genomic Analysis Tool | ||||
clever-toolkit | Anvil | Clever-toolkit is a collection of tools to discover and genotype structural variations in genomes from paired-end sequencing reads. The main software is written in C++ with some auxiliary scripts in Python. | Anvil: https://www.rcac.purdue.edu/software/clever-toolkit | Anvil: 2.4 | ||||||||||||
clhep | Aces, Faster | CLHEP (Class Library for High Energy Physics) is a library of C++ classes specifically designed for high energy physics (HEP) applications. It provides a set of utility classes for HEP-specific tasks, such as vectors, matrices, random number generation, and units of measurement. | 1. Vector and matrix classes\r 2. Random number generators\r 3. Physical constants and units\r 4. Geometry and kinematics classes\r 5. Reference counting and smart pointers\r 6. Event data model classes |
Computational Tool | High Energy Physics | Physics | C++ Library, High Energy Physics, Hep Applications | Physical Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.4.6.2 Faster: 2.4.5.1, 2.4.6.4 |
Library | |||||
climetlab | Aces | CliMetLab is a Python package aiming at simplifying access to climate and meteorological datasets, allowing users to focus on science instead of technical issues such as data access and data formats. Description Source: https://climetlab.readthedocs.io/en/latest/index.html |
climetlab is a Python library designed for easy access, manipulation, and visualization of climate data. It aims to simplify the process of working with climate datasets by providing a unified interface and tools for data exploration. | Accessing Climate Datasets, Manipulating Climate Data, Visualizing Climate Data, Convenient Data Exploration Tools | https://climetlab.readthedocs.io/en/latest/ | Library | Climate & Global Dynamics | Earth & Environmental Sciences | Python Library, Climate Data, Data Visualization | https://github.com/ecmwf/climetlab | Earth & Environmental Sciences | https://climetlab.readthedocs.io/en/latest/firststeps.html | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.12.6 | Data Analysis & Visualization | |
clip | Aces | CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs. It can be instructed in natural language to predict the most relevant text snippet, given an image, without directly optimizing for the task, similarly to the zero-shot capabilities of GPT-2 and 3. Description Source: https://github.com/openai/CLIP |
CLIP (Contrastive Language-Image Pretraining) is a framework for learning joint representations of images and text. It is designed to pretrain on large scale image-text datasets to learn a powerful visual-linguistic understanding. | 1. Pretraining on large-scale image-text datasets\r 2. Learning joint representations of images and text\r 3. Enhancing visual-linguistic understanding\r 4. Facilitating downstream tasks such as zero-shot learning, image-text retrieval, and visual question answering |
https://github.com/openai/CLIP/blob/main/notebooks/Interacting_with_CLIP.ipynb | Deep Learning | Natural Language Processing | Artificial Intelligence & Intelligent Systems | Machine Learning, Deep Learning, Image-Text Representation, Pretraining | https://openai.com/research/clip | Computer & Information Sciences | https://github.com/openai/CLIP#usage | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 20230220-Cuda-11.7.0 | Machine Learning Framework | |
clonalframeml | Anvil | ClonalFrameML is a software package that performs efficient inference of recombination in bacterial genomes. | ClonalFrameML is a software for inferring recombination in bacterial and archaeal genomes. It uses a maximum likelihood framework to detect recombination events and reconstruct the clonal relationships between individuals. | 1. Inference of recombination events in bacterial and archaeal genomes. 2. Reconstruction of clonal relationships between individuals. 3. Maximum likelihood framework for accurate estimation. | Bioinformatics, Hpc Tools | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/clonalframeml | Anvil: 1.11 | ||||||||
clp | Faster | CLP (Cbc, Lapack, and ParallelCbc) is an open-source linear programming solver that provides both a standalone solver and a framework for building custom optimization algorithms. It is designed to solve large-scale linear programming problems efficiently and offers a range of features for linear optimization. | Standalone Linear Programming Solver, Framework For Building Custom Optimization Algorithms, Efficient Solution Of Large-Scale Linear Programming Problems | Solver | Operations Research, Industrial Engineering | Linear Programming, Optimization, Large-Scale Problems, Open-Source | Engineering & Technology | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.17.7 | Optimization Software | ||||||
clust | Anvil | Clust is a fully automated method for identification of clusters (groups) of genes that are consistently co-expressed (well-correlated) in one or more heterogeneous datasets from one or multiple species. | Clust is a software for clustering heterogeneous time series data. It allows users to identify similarity patterns and group time series data together based on various criteria. | 1. Clustering heterogeneous time series data\r 2. Identifying similarity patterns among time series\r 3. Grouping time series data based on specified criteria\r 4. Analyzing patterns and trends within clusters |
Data Analysis Tool | Clustering, Time Series Data, Pattern Identification | Other Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/clust | Anvil: 1.17.0 | Clustering Software | ||||||
clustalw | Anvil | Clustalw is a general purpose multiple alignment program for DNA or proteins. | ClustalW is a widely used multiple sequence alignment program for DNA or protein sequences. It aligns multiple sequences using various algorithms to identify homologous regions and conserved motifs. | 1. Multiple sequence alignment for DNA or protein sequences\r 2. Identifies homologous regions and conserved motifs\r 3. Supports various alignment algorithms\r 4. Generates phylogenetic trees based on aligned sequences |
Tool | Bioinformatics, Sequence Alignment | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/clustalw | Anvil: 2.1 | Computational Software | ||||||
clustalw2 | Faster | ClustalW2 is a general purpose multiple sequence alignment program for DNA or proteins. It produces biologically meaningful multiple sequence alignments of divergent sequences. | Multiple Sequence Alignment For DNA Or Proteins, Phylogenetic Tree Generation, Visualization Of Alignments, Alignment Quality & Reliability Analysis | Alignment Tool | Bioinformatics, Computational Biology, Sequence Analysis | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.1 | Bioinformatics | |||||||
cluster-tools | Ookami | https://github.com/constantinpape/cluster_tools/blob/master/cluster_tools/workflows.py | https://github.com/constantinpape/cluster_tools | https://github.com/constantinpape/cluster_tools/tree/master/example | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 9.0 | ||||||||||
cm-pmix3 | Expanse, Ookami | cm-pmix3 is a lightweight, high-performance library that provides process management and control functions for large-scale computing environments. | It offers capabilities for process monitoring, reporting, and control, with support for spawning, killing, and monitoring individual processes within a job. The library is designed to work seamlessly with various job schedulers and resource managers. | https://pmix.github.io/uploads/2019/02/pmix-standard-3.1.pdf | System & Process Management | Infrastructure & Instrumentation | Other Computer & Information Sciences | Process Management, High-Performance Computing, Job Scheduling | https://pmix.github.io/standard | Engineering & Technology | https://openpmix.github.io/support/how-to/ | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Expanse: 3.1.7 Ookami: 3.1.4 |
Library | ||
cmake | Aces, Anvil, Darwin, Delta, Expanse, Faster, Kyric, Ookami, Stampede3 | CMake is the de-facto standard for building C++ code, with over 2 million downloads a month. It’s a powerful, comprehensive solution for managing the software build process. Description Source: https://cmake.org/ |
CMake is an open-source, cross-platform family of tools designed to build, test, and package software. It is used to control the software compilation process using simple platform and compiler-independent configuration files. | 1. Cross-platform build system\r 2. Automated dependency resolution\r 3. Package generation for multiple platforms\r 4. Integrated support for popular development environments\r 5. Extensible through custom modules\r 6. Supports in-place and out-of-place builds\r 7. Versatile project configuration options |
https://cmake.org/cmake/help/latest/ | Developer Tools | Software Development | Software Engineering, Systems, & Development | Build System, Cross-Platform, Software Development | https://cmake.org/ | Engineering & Technology | https://cmake.org/getting-started/, https://cmake.org/cmake/help/latest/guide/tutorial/index.html https://www.youtube.com/watch?v=wl2Srog-j7I |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/cmake Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 3.18.4, 3.20.1, 3.21.1, 3.22.1, 3.23.1, 3.24.3, 3.26.3, 3.27.6 Anvil: 3.20.0 Delta: 3.20.2, 3.27.9 Expanse: Bpzre3Q, Rc2Aosa, ... Faster: 3.11.4, 3.15.3, 3.16.4, 3.18.4, 3.20.1, 3.21.1, 3.22.1, 3.23.1, 3.24.3, 3.26.3, 3.27.6 Kyric: 3.16.2 Ookami: 3.25.2 Stampede-3: 3.28.1, 3.29.5 |
Build Automation Tools | |
cmd | Ookami | The cmd module in Python provides a framework for building interactive command line applications. It allows developers to easily create command-line interfaces by defining a set of commands and their associated functions. | 1. Enables creation of command-line interfaces. 2. Supports the definition of commands and functions. 3. Facilitates interactive sessions. 4. Provides a customizable prompt. 5. Allows command completion and history functionality. | https://support.brightcomputing.com/manuals/9.2/developer-manual.pdf | Framework | Command Line, Python Module | https://docs.nvidia.com/dgx-superpod/administration-guide-dgx-superpod/latest/cluster-management-daemon.html# | Computer & Information Sciences | https://www.hpe.com/psnow/resources/ebooks/a00113955en_us_v2/Manage_an_HSM_System_with_Bright.html | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: Cmd | Development Tools | ||||
cmjob | Expanse, Ookami | cmjob is a Python-based tool for computational materials science that aids in automating the submission of multiple jobs on high-performance computing clusters. It simplifies the process of handling multiple job submissions, tracking job statuses, and organizing job outputs. | Automates Job Submissions On Hpc Clusters, Monitors Job Statuses, Organizes Job Outputs, Facilitates Management Of Multiple Computational Jobs | https://support.brightcomputing.com/manuals/9.2/developer-manual.pdf | Hpc, Computational Materials Science, Python Library | https://docs.nvidia.com/dgx-superpod/administration-guide-dgx-superpod/latest/cluster-management-daemon.html# | https://www.hpe.com/psnow/resources/ebooks/a00113955en_us_v2/Manage_an_HSM_System_with_Bright.html | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Expanse: Cmjob Ookami: Cmjob |
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cnvkit | Anvil | CNVkit is a command-line toolkit and Python library for detecting copy number variants and alterations genome-wide from high-throughput sequencing. | CNVkit is a software toolkit for copy number variation (CNV) detection and genotyping from targeted DNA sequencing data. It is designed to handle shallow coverage whole-exome and panel target sequencing from tumor-normal pairs. | Detection & Genotyping Of Copy Number Variations (Cnvs), Handling Shallow Coverage Whole-Exome & Panel Target Sequencing Data, Analysis Of Tumor-Normal Pairs | Analysis Tool | Molecular Biology | Genetics | Bioinformatics, Hpc Tools, Computational Software | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cnvkit | Anvil: 0.9.9-Py | Genomics | ||||
cnvnator | Anvil, Faster | Cnvnator is a tool for discovery and characterization of copy number variation (CNV) in population genome sequencing data. | CNVnator is a tool designed for the detection of copy number variations (CNVs) and genotyping using whole-genome sequencing data. It is particularly useful in studying structural variations in the human genome. | Detection Of Copy Number Variations (Cnvs), Genotyping, Utilizes Whole-Genome Sequencing Data, Identification Of Structural Variations In The Genome | Tool | Structural Genomics | Genetics | Cnv Detection, Whole-Genome Sequencing, Genotyping, Structural Variations | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cnvnator Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 0.4.1 Faster: 0.4.1 |
Bioinformatics | ||||
cobaya | Faster | Cobaya is an open-source platform for Bayesian analysis of physical and cosmological models. It provides a user-friendly interface for defining models, running parameter estimation, and sampling from posterior distributions. | Bayesian Analysis Of Physical & Cosmological Models, User-Friendly Model Definition Interface, Parameter Estimation & Sampling From Posterior Distributions | Analysis | Cosmology | Astronomy & Planetary Sciences | Bayesian Analysis, Physical Models, Cosmological Models | Physical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.2.2 | Computational Tool | |||||
code-server | Faster | Code-server is a tool that allows you to run a Visual Studio Code instance in the browser, making it convenient for remote development, collaboration, and accessing your coding environment from anywhere. | Remote Development In The Browser, Access To Visual Studio Code Environment, Real-Time Collaboration Features, Support For Extensions & Plugins, Integrated Terminal For Running Commands | Development Tool | Remote Development, Visual Studio Code, Browser-Based Coding, Collaboration, Coding Environment | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 4.5.1, 4.8.3, 4.9.1, 4.19.1 | Integrated Development Environment (Ide) | |||||||
coinfinder | Anvil | Coinfinder is an algorithm and software tool that detects genes which associate and dissociate with other genes more often than expected by chance in pangenomes. | CoinFinder is a software tool designed for locating specific coins in large image datasets. It provides a user-friendly interface for efficiently searching and identifying coins based on their features. | Image Analysis For Coin Recognition, Search Functionality For Locating Specific Coins, User-Friendly Interface For Ease Of Use | Search Tool | Image Processing | Other | Image Analysis, Coin Recognition, Search Tool | Engineering & Technology | Anvil: https://www.rcac.purdue.edu/software/coinfinder | Anvil: 1.2.0 | Image Recognition | ||||
coinutils | Faster | CoinUtils is an open-source collection of classes and helper functions that are generally useful to multiple COIN-OR projects. The project includes classes for storing and manipulating sparse matrices and vectors, performing matrix factorization, parsing input files in standard formats, building representations of mathematical programs, comparing floating point numbers with a tolerance, etc. Description Source: https://www.coin-or.org/projects/#ffs-tabbed-12 |
CoinUtils is an open-source C++ library that provides utilities and tools for optimization problems. It is part of the COIN-OR project, a collection of operations research software tools. | 1. Linear and integer programming utilities\r 2. LP and MIP file format conversion tools\r 3. Mathematical programming libraries for optimization\r 4. Compatible with other COIN-OR packages like Clp and Cbc |
https://coin-or.github.io/CoinUtils/Doxygen/index.html | Optimization Software | Optimization | Applied Mathematics | Optimization, Operations Research, Mathematical Programming | https://github.com/coin-or/CoinUtils | Mathematics | https://coin-or.github.io/user_introduction.html | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.11.6 | Library | |
colabfold | Aces, Faster | ColabFold is a web-based tool that leverages artificial intelligence to predict protein structures rapidly and accurately, making cutting-edge protein folding accessible to researchers without requiring extensive computational resources. It builds on the technology of AlphaFold by DeepMind, providing a user-friendly platform for scientific exploration and discovery in the field of bioinformatics and structural biology. | ColabFold is a collaborative project that aims to bring together deep learning and biophysical modeling for protein structure prediction. It provides an easy-to-use interface for researchers to perform protein folding predictions using state-of-the-art techniques. | Combines Deep Learning & Biophysical Modeling, Protein Structure Prediction, User-Friendly Interface | https://github.com/sokrypton/ColabFold/wiki | Protein Structure Prediction Tool | Protein Structure Prediction | Bioinformatics | Protein Structure Prediction, Deep Learning, Biophysical Modeling | https://github.com/sokrypton/ColabFold | Biological Sciences | https://docs.google.com/presentation/d/1mnffk23ev2QMDzGZ5w1skXEadTe54l8-Uei6ACce8eI/edit#slide=id.p https://www.youtube.com/watch?v=Rfw7thgGTwI |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.5.2-Cuda-11.7.0 Faster: 1.3.0-Cuda-11.3.1 |
Web-Based Tool | |
colossal-ai | Faster | Colossal-AI is an open-source library that simplifies the design, training, and evaluation of complex neural networks for deep learning tasks. It provides a high-level interface that allows researchers and practitioners to easily experiment with various neural network architectures and algorithms. | 1. Simplified design of complex neural networks\r 2. Easy training and evaluation of neural network models\r 3. High-level interface for experimenting with different architectures and algorithms\r 4. Integration with popular deep learning frameworks\r 5. Supports distributed training for large-scale models |
Library | Deep Learning | Artificial Intelligence & Intelligent Systems | Deep Learning, Neural Networks, Machine Learning | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Machine Learning Library | ||||||
colossalai | Faster | ColossalAI is an open-source deep learning framework that focuses on large-scale distributed training and efficient model serving. It provides a unified platform for researchers and practitioners to build, train, and deploy deep learning models at scale. | 1. Large-scale distributed training capabilities\r 2. Efficient model serving for deployment\r 3. Unified platform for building and training deep learning models\r 4. Support for a wide range of deep learning architectures and algorithms |
Open Source | Deep Learning, Machine Learning | Artificial Intelligence & Intelligent Systems | Deep Learning Framework, Large-Scale Training, Model Serving | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.1.8-Cuda-11.3.1, 0.1.13-Cuda-11.3.1 | Deep Learning Framework | |||||
compiler | Kyric | A compiler is a special program that processes statements written in a particular programming language and turns them into machine language or "code" that a computer's processor uses. It typically acts as a translator that converts high-level programming languages into machine language. | Translation Of High-Level Programming Languages Into Machine Language, Optimization Of Code For Better Performance, Error Checking & Debugging Capabilities, Generation Of Executable Files | Compiler | Compiler, Software Development, Programming | Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Development Tools | ||||||||
compiler-rt | Kyric | compiler-rt stands for Compiler Runtime Library. It is a collection of runtime libraries that provide low-level support for compiler-generated code. It is designed to be used with the LLVM compiler infrastructure and is commonly used in conjunction with Clang. The compiler-rt libraries implement runtime parts of the language features that are not supported directly by the compiler. | Runtime Support Libraries For Compiler-Generated Code, Designed For Use With The Llvm Compiler Infrastructure, Implements Runtime Parts Of Language Features Not Directly Supported By The Compiler | Library | Software Engineering, Systems, & Development | Computer Science | Runtime Library, Compiler Support, Low-Level Support, Language Features | Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Compiler Runtime | ||||||
compiler-rt32 | Kyric | The compiler-rt32 project is a runtime library that provides functionality for compilers in the 32-bit architecture. It includes various runtime components such as sanitizers, builtins, and support libraries for handling memory operations and error detection. | 1. Memory error detection using sanitizers\r 2. Built-in functions for optimized operations\r 3. Support libraries for compiler runtime functions\r 4. Designed for 32-bit architecture compilers\r 5. Integration with compiler toolchains |
Runtime Library | Systems Software | Computer Science | Compiler, Runtime Library, 32-Bit Architecture | Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Development Library | ||||||
compiler32 | Kyric | compiler32 is a lightweight and efficient compiler software designed for compiling source code into executable programs. It supports various programming languages and optimization techniques to enhance the performance of the compiled code. | Support For Multiple Programming Languages, Optimization Techniques, Efficient Compilation Process | Development Tools | Compiler, Software Development, Programming | Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Compiler | ||||||||
compress-raw-zlib | Faster | compress-raw-zlib is a raw Zlib compression and decompression library written in C for Python, providing low-level access to Zlib compression and decompression functionality. | Key features include raw Zlib compression and decompression without any header or wrapper data, enabling direct interaction with Zlib streams. The library offers efficient compression and decompression operations for data processing. | Compression & Decompression | Compression, Decompression, Raw Zlib, Library | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.202 | Library | |||||||
comsol | Bridges-2 | COMSOL is an advanced simulation software that provides a finite element analysis, solver, and multiphysics simulation capabilities. It allows for the modeling of complex engineering and scientific problems involving coupled phenomena across fields like electromagnetics, mechanics, fluid dynamics, and chemical engineering, offering a versatile platform for both research and industrial applications. | COMSOL is a platform for modeling and simulating physics-based systems. It offers a wide range of tools for multiphysics simulations, allowing users to analyze and optimize designs in various scientific and engineering fields. | Multiphysics Simulations, Finite Element Analysis, Customizable Modeling Environment, Interactive Simulation Tools, Comprehensive Physics Libraries, Post-Processing Capabilities | https://doc.comsol.com/6.2/docserver/#!/com.comsol.help.comsol/helpdesk/helpdesk.html | Simulation Software | Engineering | Simulation, Modeling, Physics, Engineering, Optimization | https://www.comsol.com/ | Engineering & Technology | https://www.comsol.com/support/learning-center | Bridges-2: https://www.psc.edu/resources/software/comsol | Bridges-2: 6.1 | Engineering & Technology | ||
concoct | Anvil | Concoct is a program for unsupervised binning of metagenomic contigs by using nucleotide composition, coverage data in multiple samples and linkage data from paired end reads. | Concoct is a software tool designed for the binning of metagenomic contigs by utilizing nucleotide composition, coverage across multiple samples, and linkage information derived from paired-end reads. | 1. Metagenomic contig binning\r 2. Utilizes nucleotide composition, coverage, and linkage information\r 3. Supports multiple samples analysis\r 4. Facilitates the identification of microbial populations in environmental samples |
Data Analysis Tool | Metagenomics | Environmental Biology | Metagenomics, Bioinformatics, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/concoct | Anvil: 1.1.0 | Bioinformatics Tool | ||||
conda-env | Delta | Conda-env is a command-line tool that allows users to create, export, list, remove, and update conda environments. Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. | 1. Create new conda environments. 2. Export and share conda environments. 3. List existing conda environments. 4. Remove conda environments. 5. Update conda environments with new packages. | Command Line Tool | Package Management, Environment Management | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: Cegan-Py3.9.18 | Package Management | |||||||
control-freec | Anvil | Control-freec is a tool for detection of copy-number changes and allelic imbalances (including LOH) using deep-sequencing data. | Control-FREEC is a tool for detection of copy-number alterations and loss of heterozygosity in whole-genome sequencing data. | Control-FREEC is able to detect copy-number alterations, loss of heterozygosity, and estimate purity, ploidy, and infer normal contamination in tumor samples. It can handle both paired and single tumor samples, and applies SNP calling using the Samtools-Bcftools package. | Bioinformatics Tool | Cancer Genetics | Genetics | Bioinformatics, Copy Number Variation, Whole-Genome Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/control-freec | Anvil: 11.6 | Genomic Analysis Tool | ||||
cooler | Anvil | Cooler is a support library for a sparse, compressed, binary persistent storage format, also called cooler, used to store genomic interaction data, such as Hi-C contact matrices. | Cooler is a computational software package used for the analysis, normalization, and visualization of Hi-C and other chromatin interaction data. It provides tools for processing, exploring, and interpreting high-resolution chromatin interaction data. | 1. Processing Hi-C data\r 2. Normalization of chromatin interaction matrices\r 3. Visualization of chromatin interactions\r 4. Analysis and interpretation tools for Hi-C data |
Bioinformatics | Computational Software, Hi-C Data Analysis, Chromatin Interaction Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cooler | Anvil: 0.8.11 | Data Analysis & Visualization | ||||||
coordgenlibs | Aces, Faster | This is Schrödinger, Inc's 2D coordinate generation. CoordgenLibs is a computational library used for automatically generating 2D coordinates for molecular structures, facilitating their visualization and analysis in chemical informatics and drug design applications. It is part of the Schrödinger suite, designed to produce chemically meaningful and aesthetically pleasing representations of molecules. | CoordGenLibs is a set of computational chemistry libraries and tools for generating 3D coordinates for small molecules. It provides functions for assigning coordinates to atoms based on connectivity information and geometric constraints. | 1. Generation of 3D coordinates for small molecules\r 2. Connectivity-based atom coordination\r 3. Geometric constraints for accurate coordinate assignment\r 4. Integration with various computational chemistry workflows |
https://github.com/schrodinger/coordgenlibs/blob/master/README.md | Chemical Informatics | Computational Chemistry, 3D Coordinate Generation, Small Molecules | https://github.com/schrodinger/coordgenlibs | Chemical Sciences | https://github.com/schrodinger/coordgenlibs/tree/master/example_dir | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.0.1 Faster: 3.0.1 |
Library | |||
coverage | Aces | Coverage is a tool used to measure the extent to which the source code of a program has been tested. It is often used in software development to assess the quality and thoroughness of testing by determining which parts of the code have been executed during testing. | Measures Code Coverage To Evaluate The Effectiveness Of Test Suites, Identifies Parts Of The Code That Have Not Been Tested, Helps Developers Understand The Quality Of Their Testing Efforts, Can Be Used To Improve Test Coverage & Identify Potential Gaps In Testing | Tool | Code Coverage, Testing, Software Development, Quality Assurance | Engineering & Technology, Computer & Information Sciences, Software Engineering, Systems, & Development | Aces: https://hprc.tamu.edu/software/aces/ | Testing & Quality Assurance | ||||||||
coverm | Anvil | Coverm is a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications. | COVERM is a software tool for the analysis of metagenomic data, particularly for evaluating the coverage and abundance of genes or sequences within metagenomes. | Some core features of COVERM include calculating coverage and abundance metrics for genes in metagenomic data, assessing sample completeness, providing visualizations for coverage profiles, and enabling users to compare different samples. | Genomic Analysis Tool | Bioinformatics | Metagenomics, Bioinformatics, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/coverm | Anvil: 0.6.1 | Computational Tool | |||||
covgen | Anvil | Covgen creates a target specific exome_full192.coverage.txt file required by MutSig. | CovGen is a software tool designed for generating coverage statistics from sequencing data, particularly useful in the field of bioinformatics for analyzing the depth and distribution of sequencing coverage across the genome. | 1. Calculates sequencing coverage statistics\r 2. Visualizes coverage data in graphical format\r 3. Facilitates comparison of coverage between samples\r 4. Supports various sequencing platforms and data formats\r 5. Automates the process of calculating coverage metrics\r 6. Intuitive and user-friendly interface for ease of use |
Analysis Tool | Sequencing Data Analysis, Coverage Statistics, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/covgen | Anvil: 1.0.2 | Bioinformatics Tool | ||||||
cp2k | Aces, Anvil, Bridges-2, Expanse, Faster, Ookami, Stampede3 | CP2K is a quantum chemistry and solid state physics software package that can perform atomistic simulations of solid state, liquid, molecular, periodic, material, crystal, and biological systems. Description Source: https://www.cp2k.org/ |
CP2K is an open-source quantum chemistry and solid state physics software package designed to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It can be used to study a wide range of properties, including electronic structures, molecular dynamics, and vibrational spectra. | Key features of CP2K include density functional theory (DFT) calculations, molecular dynamics simulations, efficient algorithms for large-scale parallel computations, advanced basis sets, and support for various functionals and dispersion corrections. It also offers tools for studying solvation effects, band structures, and NMR properties. | https://manual.cp2k.org/trunk/ | Molecular Simulation | Condensed Matter Physics, Atomic, Molecular, & Optical Physics | Physical Sciences | Computational Chemistry, Quantum Mechanics, Molecular Dynamics | https://www.cp2k.org/ | Physical Sciences | https://www.cp2k.org/exercises | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/cp2k Bridges-2: https://www.psc.edu/resources/software/cp2k Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 9.1-Lib, 9.1, 2022.1-Lib, 2022.1, 2023.1-Cuda-11.8.0, 2023.1-Lib, 2023.1-Plumed-2.9.0, 2023.1 Anvil: 8.2 Bridges-2: 7.1-Intel, 8.1-Gcc10.2.0-Openmpi4.0.5, ... Expanse: Ub7Xgkh-Omp Faster: 8.2, 2023.1-Cuda-11.8.0 Ookami: Gcc13.2/2024.1 Stampede-3: 2024.1.1 |
Computational Software | |
cpe | Delta, Ookami | Cray Compiling Environment (CCE) consists of compilers, libraries, and utilities that perform code analysis during compilation and automatically generate highly optimized code. Compilers support numerous command-line arguments to enable manual control over compiler behavior and optimization. Supported languages include Fortran, C and C++, and UPC (Unified Parallel C). Description Source: https://cpe.ext.hpe.com/docs/cce/index.html |
CPE (Common Platform Enumeration) is a standardized method to describe and identify classes of applications, operating systems, and hardware devices in a consistent format. It provides unique identifiers for these entities to facilitate accurate and efficient information exchange between different security tools and databases. | 1. Standardized identification and description of software and hardware entities.\r 2. Facilitates interoperability between security tools and databases.\r 3. Assigns unique identifiers to each software, operating system, and hardware device.\r 4. Supports accurate and efficient information exchange in the cybersecurity domain. |
https://cpe.ext.hpe.com/docs/cce/index.html#cce | Tool | Software Engineering, Systems, & Development | Computer Science | Software Identification, Cybersecurity, Information Exchange | https://www.hpe.com/psnow/doc/a50002303enw | Computer & Information Sciences | https://cpe.ext.hpe.com/docs/guides/CPE/index_user_guides.html | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Delta: 23.09 Ookami: 23.02(Default) |
Security Software | |
cpe-nosve | Ookami | NOS/VE is a proprietary operating system of CDC in close relation to the well-renowned MULTICS operating system of MIT, see www.multicians.org. It is a virtual memory operating system, employing the 64-bit virtual mode of the Cyber 960 as opposed to the 60-bit real memory mode (CDC 6600/7600 mode) used by the NOS operating system. Both systems run concurrently on a single CPU. Description Source: https://www.cray-cyber.org/old/documentation/nosve_howto.php |
CPE-NOsvE (Canonical Polyadic Decomposition-based Network Observation for Structure Validation and Elucidation) is a computational tool for network structure elucidation and validation using canonical polyadic decomposition (CPD) analysis. It is designed to infer the underlying structure of complex networks from observed data, helping researchers better understand and validate network architectures. | 1: Utilizes canonical polyadic decomposition (CPD) analysis for network structure inference 2: Validates and elucidates complex network structures, 3: Assists in understanding the underlying architecture of networks from observed data | https://www.cray-cyber.org/old/documentation/nosve_howto.php | Computational Software, Network Analysis, Data Validation, Structure Elucidation | https://www.cray-cyber.org/old/documentation/nosve_howto.php | Computer & Information Sciences | https://cray-cyber.org/old/systems/cy960_shortguide.php | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 21.03 | |||||
cppunit | Faster | CppUnit is a C++ unit testing framework designed to assist in writing and running automated test suites for C++ code. It is based on the xUnit architecture and is similar in functionality to JUnit for Java. | Supports Test Fixtures, Test Suites, Assertions, Test Runners, Output Validation | Library | Unit Testing, C++ | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.15.1 | Testing Framework | |||||||
cppy | Aces, Faster | A small C++ header library which makes it easier to write Python extension modules. The primary feature is a PyObject smart pointer which automatically handles reference counting and provides convenience methods for performing common object operations. Description Source: https://github.com/nucleic/cppy |
C++ embedded Python library to seamlessly interact with C++ and Python code within the same application. | Embed Python Interpreter In C++ Applications, Call Python Functions From C++ Code, Exchange Data Between C++ & Python Seamlessly | https://cppy.readthedocs.io/en/latest/ | Integration Tool | C++, Python, Embedded Python, Interoperability | https://github.com/nucleic/cppy | Computer & Information Sciences | https://cppy.readthedocs.io/en/latest/installation.html#using-cppy-in-an-extensions | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.1.0, 1.2.1 Faster: 1.1.0, 1.2.1 |
Software Library | |||
cpu | Expanse | CPU (Central Processing Unit) is a hardware component of a computer that executes instructions and performs calculations. It is considered the brain of the computer and is responsible for carrying out tasks and running applications. | 1. Executes instructions from computer programs\r 2. Performs arithmetic and logic operations\r 3. Manages data and input/output operations\r 4. Controls other hardware components\r 5. Supports multitasking and multiprocessing |
Component | Hardware, Computing, Technology | Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 0.15.4, 0.17.3B | Hardware | |||||||
cramino | Anvil | Cramino is a tool for quick quality assessment of cram and bam files, intended for long read sequencing. | Cramino is a software tool designed for computational chemistry simulations and molecular dynamics studies. | Molecular dynamics simulations, Quantum chemistry calculations, Energy minimization, Molecular visualization, Trajectory analysis | Scientific Software | Chemical Sciences | Physical Sciences | Computational Chemistry, Molecular Dynamics, Quantum Chemistry | Chemical Sciences | Anvil: https://www.rcac.purdue.edu/software/cramino | Anvil: 0.9.6 | Simulation Software | ||||
cray | Delta | Cray is a supercomputing company well-known for its high-performance computing systems and solutions. Cray supercomputers are designed to handle complex computational tasks and large-scale scientific simulations. | 1. High-performance computing capabilities\r 2. Scalability to handle massive workloads\r 3. Advanced parallel processing architecture\r 4. Support for various scientific and engineering applications\r 5. Efficient use of compute resources |
Hpc Tool | Supercomputing, High-Performance Computing, Scientific Computing | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Computational Software | ||||||||
crisprcasfinder | Anvil | Crisprcasfinder is an updated, improved, and integrated version of CRISPRFinder and CasFinder. | CRISPRCasFinder is a tool for the identification of CRISPR arrays and Cas proteins in prokaryotic genomes. It uses a combination of CRISPR technology and Cas protein identification to accurately identify CRISPR-Cas systems in bacterial and archaeal genomes. | 1. Detection of CRISPR arrays in bacterial and archaeal genomes. 2. Identification of Cas proteins associated with CRISPR loci. 3. Prediction of potential CRISPR-Cas systems configurations. 4. Visualization of CRISPR arrays and Cas proteins in genomic context. | Genome Analysis Tool | Bioinformatics | Genetics | Genome Analysis, Crispr-Cas Systems, Prokaryotic Genomes | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/crisprcasfinder | Anvil: 4.2.20 | Bioinformatics Tool | ||||
crispresso2 | Anvil | CRISPResso2 is a software pipeline designed to enable rapid and intuitive interpretation of genome editing experiments. | CRISPResso2 is a software tool for the analysis of CRISPR-Cas9 genome editing outcomes from deep sequencing data. It provides researchers with a comprehensive and user-friendly platform to quantify editing efficiency, visualize editing patterns, and assess indel formation and repair mechanisms. | Quantification Of Editing Efficiency, Visualization Of Editing Patterns, Assessment Of Indel Formation & Repair Mechanisms, Identification Of Off-Target Effects | Analysis Tool | Molecular Biology, Genetics | Biochemistry & Molecular Biology, Genetics | Crispr, Genome Editing, Sequencing Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/crispresso2 | Anvil: 2.2.8, 2.2.9, 2.2.10, 2.2.11A | Bioinformatics | ||||
crispritz | Anvil | Crispritz is a software package containing 5 different tools dedicated to perform predictive analysis and result assessement on CRISPR/Cas experiments. | CRISPRitz is a web-based software tool for designing and analyzing CRISPR/Cas9 guide RNAs. It allows users to design guide RNAs for gene knockout, gene editing, and transcriptional activation with high specificity and efficiency. | Guide RNA Design For Gene Knockout, Guide RNA Design For Gene Editing, Guide RNA Design For Transcriptional Activation, High Specificity & Efficiency, Web-Based Interface | Web-Based Tool | Crispr/Cas9, Guide RNA Design, Genome Editing, Molecular Biology | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/crispritz | Anvil: 2.6.5 | Bioinformatics Tool | ||||||
cross_match | Anvil | cross_match is a general purpose utility for comparing any two DNA sequence sets using a 'banded' version of swat. | Cross_Match is a software package used for aligning two lists of objects, usually representing detected sources or astronomical catalogs, in order to identify matching or related entries. | Alignment Of Two Lists Of Objects, Identification Of Matching Entries, Astronomical Applications, Handling Of Astronomical Catalog Data | Matching Tool | Astronomy | Astronomy & Planetary Sciences | Alignment, Astronomy, Cataloging, Data Processing | Physical Sciences | Anvil: https://www.rcac.purdue.edu/software/cross_match | Anvil: 1.090518 | Data Processing | ||||
crossmap | Anvil | Crossmap is a program for genome coordinates conversion between different assemblies. | CrossMap is a versatile tool for genome coordinates conversion between different assemblies. It provides a unified and user-friendly interface for mapping features such as genomic intervals, gene coordinates, and other genomic annotations between various genome assemblies. | Conversion Of Genome Coordinates Between Different Assemblies, Mapping Of Genomic Annotations & Features, User-Friendly Interface | Bioinformatics Tool | Genome Assembly & Annotation | Genomics | Genome Assembly, Genomics, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/crossmap | Anvil: 0.6.3 | Utility Tool | ||||
cryosparc | Aces, Darwin | CryoSPARC is a comprehensive software platform for cryo-EM data processing that enables high-resolution structure determination of biological macromolecules. | Automated Particle Picking, 3D Heterogeneity Analysis, Ab-Initio 3D Reconstruction, High-Resolution Refinement, Model Building & Validation | Cryo-Em Software | Structural Biology | Biophysics | Cryo-Em, Biological Macromolecules, Structural Biology, Data Processing | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 4.2.1 | Data Processing | |||||
cryptography | Aces, Faster | cryptography is a package designed to expose cryptographic primitives and recipes to Python developers. | Cryptography is the practice and study of techniques for secure communication in the presence of third parties. It involves creating and analyzing protocols that prevent third parties or the public from reading private messages. | Encryption, decryption, secure communication, digital signatures, authentication, key generation | Software | Security, Privacy, Encryption, Decryption | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 41.0.1, 41.0.4, 41.0.5 Faster: 41.0.1 |
Tools | ||||||
cryptsetup | Kyric | cryptsetup is a utility used to conveniently set up disk encryption based on the Dm-crypt kernel module. It allows users to easily configure encrypted block devices using LUKS (Linux Unified Key Setup), manage cryptographic volumes, and interact with encrypted volumes. | Disk Encryption Setup, Luks Support, Cryptographic Volume Management, Interaction With Encrypted Volumes | https://github.com/grahamgilbert/crypt/blob/master/README.md | System Software | Disk Encryption, Data Security, Cryptography, Linux | https://github.com/grahamgilbert/crypt | Computer & Information Sciences | https://github.com/grahamgilbert/crypt/blob/master/Example%20Crypt%20Profile.mobileconfig | Utility | ||||||
csvkit | Anvil | csvkit is a suite of command-line tools for converting to and working with CSV, the king of tabular file formats. | csvkit is a suite of command-line tools for converting and working with CSV files in various ways. | 1. Convert CSV files between different formats.\r 2. Query CSV files using SQL.\r 3. Clean and manipulate CSV files.\r 4. Combine and merge CSV files.\r 5. Summarize, analyze, and visualize CSV data.\r 6. Work with large CSV files efficiently. |
Command-Line Tool | Csv, Command-Line, Data Manipulation, Data Analysis | Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/csvkit | Anvil: 1.1.1 | Data Manipulation Tools | ||||||
csvtk | Anvil | Csvtk is a cross-platform, efficient and practical CSV/TSV toolkit. | csvtk is a cross-platform, efficient, and practical CSV/TSV toolkit for working with flat files. It aims to make it easy to work with csv and tsv data, providing a variety of functionalities for processing, cleaning, and analyzing tabular data. | Convert Between Csv & Tsv Formats, Merge Multiple Files By Rows Or Columns, Filter Rows Or Columns Based On Specified Conditions, Sort Data Based On Specified Columns, Perform Basic Statistics On Columns, Join Tables Based On Specified Keys, Extract Specific Columns Or Rows, Split Large Files Into Smaller Chunks | Command Line Tool | Data Manipulation, Tabular Data, Data Analysis, Data Processing | Other Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/csvtk | Anvil: 0.23.0, 0.25.0 | Data Analysis Tool | ||||||
cti | Delta | CTI (Common Threat Intelligence) is an open source library designed to parse and manipulate structured threat intelligence information. It provides a set of APIs to work with different threat intelligence data formats and supports the serialization of data into various formats. | Parsing Structured Threat Intelligence Data, Manipulating Threat Intelligence Information, Support For Various Threat Intelligence Data Formats, Serialization Of Data Into Different Formats | Threat Intelligence | Threat Intelligence, Data Parsing, Open Source | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Library | ||||||||
cubegui | Aces | Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of the dimensions (i) performance metric, (ii) call path, and (iii) system resource. Each dimension can be represented as a tree, where non-leaf nodes of the tree can be collapsed or expanded to achieve the desired level of granularity. This module provides the Cube graphical report explorer. | Cubegui is a graphical user interface (GUI) software designed for visualizing and analyzing volumetric data in computational chemistry and materials science. | Cubegui allows users to load, visualize, and manipulate volumetric data files in various formats. It provides tools for interactive exploration of molecular and crystal structures, electron densities, molecular orbitals, and other properties derived from quantum mechanical calculations. Users can customize visual representations, create animations, and perform analysis on the volumetric data. | Graphical User Interface (Gui) | Physical Chemistry | Chemical Sciences | Gui Software, Volumetric Data Visualization, Computational Chemistry, Materials Science | Natural Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 4.8.2 | Data Visualization | ||||
cubelib | Aces | Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of the dimensions (i) performance metric, (ii) call path, and (iii) system resource. Each dimension can be represented as a tree, where non-leaf nodes of the tree can be collapsed or expanded to achieve the desired level of granularity. This module provides the Cube general purpose C++ library component and command-line tools. | cubelib is a C++ library for parallel reduction operations on multi-dimensional arrays using CUDA. | cubelib provides efficient implementations of parallel reduction operations such as sum, min, max, and custom-defined reduction operators on multi-dimensional arrays. It is optimized for CUDA-enabled GPUs and supports various data types and reduction strategies for improved performance. | Computational Software | Parallel Computing | Computer Science | Software Library, C++, Cuda, Parallel Computing, Multi-Dimensional Arrays | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 4.8.1, 4.8.2 | Library | ||||
cubewriter | Aces | Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of the dimensions (i) performance metric, (ii) call path, and (iii) system resource. Each dimension can be represented as a tree, where non-leaf nodes of the tree can be collapsed or expanded to achieve the desired level of granularity. This module provides the Cube high-performance C writer library component. | Cubewriter is a software tool that enables researchers to organize, write, and format scientific papers efficiently. | Key features of Cubewriter include template-based formatting for various journals, real-time collaboration and feedback, references management, version control, and integration with LaTeX for advanced document customization. | Productivity Tool | Scientific Writing, Document Formatting, Research Collaboration, References Management | Other Natural Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 4.8.2 | Research & Writing Tools | ||||||
cuda | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Jetstream, Ookami | The NVIDIA® CUDA® Toolkit provides a development environment for creating high performance GPU-accelerated applications. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. Description Source: https://developer.nvidia.com/cuda-toolkit |
CUDA is a parallel computing platform and application programming interface model created by NVIDIA. It allows software developers to use a CUDA-enabled graphics processing unit for general-purpose processing. | Parallel Computing Platform, Programming Model For Nvidia Gpus, Support For C, C++, & Fortran Programming Languages, Unified Memory For Simplified Memory Management, Performance Optimization Tools | https://docs.nvidia.com/cuda/ | Compiler | Parallel Computing, Gpu Programming, High Performance Computing, Software Development | https://developer.nvidia.com/cuda-zone | Computer & Information Sciences | https://developer.nvidia.com/how-to-cuda-c-cpp https://youtu.be/H3AQnlpxk0c https://youtu.be/_JgNA82325I https://youtu.be/dB5Jxwj0PDw https://developer.nvidia.com/cuda-toolkit |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/cuda Bridges-2: https://www.psc.edu/resources/software/cuda Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 11.1.1, 11.3.1, 11.4.1, 11.7.0, 11.8.0, 12.0.0, 12.1.0, 12.1.1, 12.2.0, 12.2.2, 12.3.0, 12.3.2 Anvil: 11.0.3, 11.2.2, 11.4.2, 12.0.1 Bridges-2: 9.2.0, 10.0.0, 10.2.0, 11.7.1, 12.4.0 Delta: 11.3.1, 11.7.0, 11.8.0.Testing, 11.8.0, ... Expanse: Blza2Ps, Ouuq5Zm Faster: 10.1.243, 11.0.2, 11.1.1, 11.2.2, 11.3.1, 11.4.1, 11.4.2, 11.5.0, 11.6.0, 11.7.0, 11.8.0, 12.0.0, ... Ookami: Toolkit/11.2 |
Development Tools | |||
cuda-dcgm | Expanse | NVIDIA's Data Center GPU Manager (DCGM) is a suite of tools for managing and monitoring GPU devices in data center environments. It provides real-time monitoring, troubleshooting, and diagnostics capabilities. | Real-Time Monitoring Of Gpu Performance Metrics, Alerting & Notification Of Hardware Errors & Failures, Policy-Based Power & Temperature Management, Historical Data Collection For Analysis & Reporting | Monitoring Tool | Gpu Management, Monitoring, Diagnostics, Data Center, Nvidia | Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 3.1.3.1 | Device Management | |||||||
cuda-quantum | Anvil | cuda-quantum is a CUDA-accelerated quantum computing simulator designed to efficiently simulate quantum circuits on NVIDIA GPUs. It provides a high-performance platform for simulating large-scale quantum computations with a focus on speed and scalability. | Cuda-Accelerated Quantum Computing Simulator, Efficiently Simulates Quantum Circuits On Nvidia Gpus, High-Performance Platform For Simulating Large-Scale Quantum Computations, Emphasis On Speed & Scalability | Quantum Computing Simulator | Artificial Intelligence & Intelligent Systems | Computer Science | Quantum Computing, Cuda-Accelerated, Quantum Simulator, Nvidia Gpu, High-Performance Computing | Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/cuda-quantum | Anvil: 0.4.0 | Simulation & Modeling | |||||
cuda-samples | Aces, Faster | Samples for CUDA Developers which demonstrates features in CUDA Toolkit | cuda-samples is a collection of CUDA code samples and examples provided by NVIDIA. These samples cover a wide range of CUDA programming concepts and techniques, serving as useful resources for developers to learn and practice GPU programming using CUDA. | Diverse Collection Of Cuda Code Samples, Covers Various Cuda Programming Concepts & Techniques, Helps Developers Learn & Practice Gpu Programming, Provides Hands-On Examples For Cuda Programming | Code Sample Repository | Cuda, Gpu Programming, Code Samples, Nvidia | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 12.1-Cuda-12.1.1 Faster: 12.1-Cuda-12.1.1 |
Developer Tools | ||||||
cuda10.2 | Expanse | CUDA is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). Note: This package does not currently install the drivers necessary to run CUDA. These will need to be installed manually. | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 10.2.89 | ||||||||||||
cuda11.7 | Expanse | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 11.7.1 | |||||||||||||
cudacore | Aces, Faster | CUDA (formerly Compute Unified Device Architecture) is a parallel computing platform and programming model created by NVIDIA and implemented by the graphics processing units (GPUs) that they produce. CUDA gives developers access to the virtual instruction set and memory of the parallel computational elements in CUDA GPUs. Description Source: https://hprc.tamu.edu/software/aces/# |
cudacore is a high-performance computational software that leverages GPU (Graphics Processing Unit) computing through CUDA (Compute Unified Device Architecture) for accelerated processing of scientific and engineering applications. | 1. Utilizes GPU computing power for parallel processing\r 2. Supports CUDA programming model for high-performance computing\r 3. Accelerates complex calculations in scientific and engineering domains\r 4. Enhances computational efficiency and speed for diverse applications |
https://docs.nvidia.com/cuda/cuda-c-programming-guide/ | High-Performance Computing Tool | High-Performance Computing | Other Engineering & Technologies | Computational Software, Cuda, Gpu Computing, Scientific Computing, Engineering Applications | https://github.com/NVIDIA/cccl | Engineering & Technology | https://nvdam.widen.net/s/brxsxxtskb/dli-learning-journey-2009000-r5-web | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 11.1.1 Faster: 11.0.2, 11.1.1, 11.4.1 |
Computational Software | |
cudf | Aces, Faster | cuDF is a GPU DataFrame library for loading joining, aggregating, filtering, and otherwise manipulating data. cuDF leverages libcudf, a blazing-fast C++/CUDA dataframe library and the Apache Arrow columnar format to provide a GPU-accelerated pandas API. Description Source: https://github.com/rapidsai/cudf |
CUDF is part of the RAPIDS suite of open-source software libraries and APIs built on CUDA. It provides a DataFrame manipulation library leveraging GPU acceleration for loading, joining, aggregating, filtering, and otherwise manipulating tabular data. | 1. Distributed DataFrames for larger-than-memory datasets\r 2. GPU-accelerated DataFrame operations such as sorting, filtering, joining, and aggregating\r 3. Easily integrates with other RAPIDS components like cuML for machine learning tasks\r 4. Can handle complex data operations on large datasets efficiently and effectively\r 5. Supports a wide variety of file formats for data ingestion and export |
https://docs.rapids.ai/api/cudf/stable/user_guide/api_docs/ | Library | Dataframe, Gpu Acceleration, Data Manipulation | https://github.com/rapidsai/cudf | Computer & Information Sciences, Artificial Intelligence & Intelligent Systems | https://docs.rapids.ai/api/cudf/stable/user_guide/10min/ https://www.youtube.com/watch?v=lV7rtDW94do, |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 23.04.0, 23.08.00 Faster: 23.04.0 |
Data Processing & Analysis | |||
cudnn | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster | The NVIDIA CUDA® Deep Neural Network (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, attention, matmul, pooling, and normalization. Description Source: https://docs.nvidia.com/cudnn/index.html |
The NVIDIA CUDA Deep Neural Network library (cuDNN) is a GPU-accelerated library for deep neural networks. It provides highly optimized implementations of common deep learning operations. | 1. GPU-accelerated deep neural network library\r 2. Optimized implementations of deep learning operations\r 3. Supports frameworks like TensorFlow, PyTorch, and MXNet\r 4. Enables faster training of deep learning models\r 5. Includes functions for convolution, pooling, normalization, and activation layers |
https://docs.nvidia.com/cudnn/index.html | Deep Learning Accelerator | Deep Learning | Artificial Intelligence & Intelligent Systems | Deep Learning, Artificial Intelligence, Machine Learning, Gpu Acceleration, Neural Networks | https://developer.nvidia.com/cudnn | Computer & Information Sciences | https://docs.nvidia.com/deeplearning/cudnn/installation/overview.html https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn_765/cudnn-developer-guide/index.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/cudnn Bridges-2: https://www.psc.edu/resources/software/cudnn Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 8.0.4.30-Cuda-11.1.1, 8.2.1.32-Cuda-11.3.1, 8.2.2.26-Cuda-11.4.1, 8.4.1.50-Cuda-11.7.0, 8.6.0.163-Cuda-11.8.0, ... Anvil: Cuda-11.0_8.0, Cuda-11.2_8.1, Cuda-11.4_8.2, Cuda-12.0_8.8 Bridges-2: 8.0.4 Delta: 8.4.1.50, 8.9.0.131 Expanse: Tdvkbaf, ... Faster: 7.6.4.38, 8.0.4.30-Cuda-11.0.2, 8.0.4.30-Cuda-11.1.1, 8.1.0.77-Cuda-11.2.2, 8.2.1.32-Cuda-11.3.1, 8.2.2.26-Cuda-11.4.1, ... |
Library | |
cue-login-env | Anvil, Delta, Expanse | XSEDE Operations and User Services groups recommend implementation of the cue-login-env module by SPs with XRAC allocated resources (at any SP Level). This module will provide variables containing resource information (e.g. hostname), reference location information (e.g. URLs to documentation, paths to community spaces) as well as defining the user's Home, Work & Scratch directories and other file spaces. Description Source: https://software.xsede.org/xsede-software-and-service-component/common-user-environment-cue |
Cue-login-env is a Python library that provides an easy way to configure user-specific environments within shared servers or computing clusters. It helps users manage their environment variables, aliases, and paths without interfering with the system-wide configurations. | Configuring User-Specific Environment Variables, Managing User-Specific Paths & Aliases, Isolating User Environments From System-Wide Configurations, Simplifying Environment Setup On Shared Servers Or Computing Clusters | https://hdl.handle.net/2142/75910 | Python Library | Python Library, User-Specific Environment, Shared Servers, Computing Clusters | https://software.xsede.org/xsede-software-and-service-component/common-user-environment-cue | Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/cue-login-env Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 1.1 Delta: 1.0 Expanse: Cue-Login-Env |
Development Tools | ||||
cufflinks | Anvil, Expanse | Cufflinks assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one, taking into account biases in library preparation protocols. Description Source: https://cole-trapnell-lab.github.io/cufflinks/ |
Cufflinks assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. | Transcript Assembly, Abundance Estimation, Differential Expression Analysis, Regulation Testing | https://cole-trapnell-lab.github.io/cufflinks/cufflinks/index.html | Tool | Sciences | Biology | RNA-Seq, Transcriptomics, Bioinformatics | https://cole-trapnell-lab.github.io/cufflinks/ | Biological Sciences | https://cole-trapnell-lab.github.io/cufflinks/getting_started/ | Anvil: https://www.rcac.purdue.edu/software/cufflinks Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 2.2.1 Expanse: 2.2.1 |
Bioinformatics | |
cunit | Aces, Faster | Automated testing framework for C. | CUnit is a lightweight C unit testing framework for automated testing of C code. It provides an easy-to-use framework for writing test cases and test suites to verify the correct functioning of C programs. | Supports Various Assertion Styles, Test Case Management, Logging & Reporting Of Test Results, Integration With Build Systems, Extensible & Customizable For Specific Testing Needs | Testing Framework | Unit Testing, C Programming, Development Tools | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.1-3 Faster: 2.1-3 |
Testing | ||||||
cupy | Aces, Faster | CuPy is an open-source library that provides GPU-accelerated computing with Python. It is built as a drop-in replacement for NumPy and works seamlessly with other libraries in the Python ecosystem. | Gpu-Accelerated Computing With Python, Drop-In Replacement For Numpy, Seamless Integration With Python Libraries | Gpu Computing | Python Library, Gpu Computing, Numpy Replacement | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 11.4.0-Cuda-11.4.1 Faster: 11.4.0-Cuda-11.4.1 |
Library | |||||||
cuquantum-appliance | Anvil | Anvil: https://www.rcac.purdue.edu/software/cuquantum-appliance | Anvil: 23.03 | |||||||||||||
curl | Aces, Anvil, Expanse, Faster, Kyric, Ookami | cURL is a command line tool and library for transferring data with URLs. Description Source: https://curl.se/ |
curl is a command-line tool and library for transferring data with URLs. It supports various protocols including HTTP, HTTPS, FTP, FTPS, SCP, SFTP, and more. It is widely used in scripting and automation tasks, as well as for debugging network issues. | Supports Various Protocols Like Http, Ftp, Scp, Sftp, Etc., Allows For Easy Transfer Of Data With Urls, Command-Line Tool For Scripting & Automation Tasks, Highly Customizable With Many Options & Configurations | https://curl.se/docs/ | Networking Tool | Networking, Data Transfer, Command-Line, Scripting | https://curl.se/ | Computer & Information Sciences, Other Computer & Information Sciences | https://curl.se/docs/tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/curl Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 7.72.0, 7.76.0, 7.78.0, 7.83.0, 7.86.0, 8.0.1, 8.3.0 Anvil: 7.76.1 Expanse: 7.72.0 Faster: 7.60.0, 7.66.0, 7.69.1, 7.72.0, 7.76.0, 7.78.0, 7.83.0, 7.86.0, 8.0.1, 8.3.0 Ookami: 7.85.0 |
Command-Line Tool | |||
cusparselt | Aces, Faster | NVIDIA cuSPARSELt is a high-performance CUDA library dedicated to general matrix-matrix operations in which at least one operand is a sparse matrix | CusparseLT library is a lightweight version of NVIDIA's cuSPARSE library designed for sparse matrix operations on NVIDIA GPUs. It offers high-performance accelerated computation for sparse matrix manipulation in GPU-accelerated applications. | 1. Sparse matrix-vector multiplication (SpMV)\r 2. Sparse matrix solution (Ax = b) for linear systems\r 3. Support for various sparse matrix formats\r 4. GPU acceleration for faster computation\r 5. Integration with CUDA programming model |
Computational Software | Applied Computer Science | Computer Science | Sparse Matrix Operations, Gpu Acceleration, Linear Algebra, Cuda Programming | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.5.0.1-Cuda-12.2.2 Faster: 0.3.0.3-Cuda-11.4.1 |
Library | ||||
cusz | Faster | CUSZ is a fast and memory-efficient software tool for clustering and annotating large single-cell RNA-seq datasets. | CUSZ offers advanced clustering algorithms and annotation methods tailored for analyzing single-cell RNA-seq data. It can handle large datasets with efficiency and scalability while providing accurate and interpretable results. | Bioinformatics | Single-Cell RNA Sequencing | Cell Biology | Single-Cell RNA-Seq, Clustering, Annotation | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.3.1 | Data Analysis | |||||
cutadapt | Aces, Anvil, Bridges-2, Faster | Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads. Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter single-end and paired-end reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Cutadapt can also demultiplex your reads. Description Source: https://cutadapt.readthedocs.io/en/stable/ |
cutadapt removes adapter sequences from high-throughput sequencing reads. It finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads. | Removes Adapter Sequences From High-Throughput Sequencing Reads, Identifies & Trims Various Types Of Unwanted Sequences, Flexibility In Specifying Adapter Sequences & Error Rates, Support For Various Sequencing Platforms | https://cutadapt.readthedocs.io/en/stable/reference.html | Sequence Analysis Tool | Bioinformatics, Ngs, Sequence Analysis, Genomics | https://github.com/marcelm/cutadapt | Biological Sciences | https://cutadapt.readthedocs.io/en/stable/guide.html https://cutadapt.readthedocs.io/en/stable/recipes.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/cutadapt Bridges-2: https://www.psc.edu/resources/software/cutadapt Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.5 Anvil: 2.10, 3.4, 3.7 Bridges-2: 2.10 Faster: 3.4, 3.5 |
Bioinformatics Tool | |||
cutensor | Aces, Delta, Faster | NVIDIA cuTENSOR is a GPU-accelerated tensor linear algebra library for tensor contraction, reduction, and elementwise operations. Using cuTENSOR, applications can harness the specialized tensor cores on NVIDIA GPUs for high-performance tensor computations and accelerate deep learning training and inference, computer vision, quantum chemistry, and computational physics workloads. Description Source: https://developer.nvidia.com/cutensor |
cuTensor is a CUDA-accelerated library for tensor operations in NVIDIA GPUs. It provides optimized implementations for tensor contractions and element-wise operations, allowing for efficient computation of large-scale tensor operations in parallel. | 1. Highly optimized tensor contractions\r 2. Element-wise operations for tensors\r 3. Utilizes CUDA for GPU acceleration\r 4. Efficient computation of large-scale tensor operations\r 5. Supports various tensor data types |
https://docs.nvidia.com/cuda/cutensor/latest/api/index.html | Computational Software | High-Performance Computing (Hpc) | Applied Computer Science | Cuda, Gpu Acceleration, Tensor Operations, Parallel Computing | https://developer.nvidia.com/cutensor | Computer & Information Sciences | https://docs.nvidia.com/cuda/cutensor/latest/user_guide.html#user-guide-label https://docs.nvidia.com/cuda/cutensor/latest/getting_started.html#getting-started-label |
Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.6.1.5-Cuda-11.4.1, 1.6.1.5-Cuda-11.7.0, 1.7.0.1-Cuda-12.0.0 Delta: 1.5.0.3 Faster: 1.6.1.5-Cuda-11.4.1, 1.6.1.5-Cuda-11.7.0 |
Library | |
cuttlefish | Anvil | Cuttlefish is a fast, parallel, and very lightweight memory tool to construct the compacted de Bruijn graph from sequencing reads or reference sequences. | Cuttlefish is a software package that enables users to efficiently simulate imaging systems in ray-tracing simulations, particularly to model the performance of optical systems. | Ray-Tracing Simulations, Modeling Optical Systems, Simulation Of Imaging Systems | Software Simulation, Optical Systems, Ray Tracing | Physical Sciences | Anvil: https://www.rcac.purdue.edu/software/cuttlefish | Anvil: 2.1.1 | ||||||||
cxxopts | Stampede3 | A lightweight C++ library for parsing command line arguments, inspired by Python's argparse library. | Provides a simple API for defining and parsing command line arguments in C++ applications. Supports a wide range of argument types, such as bool, string, integer, floating-point numbers, and custom data types. Allows specifying required arguments, default values, and help text. Enables grouping of options, subcommands, and handling positional arguments. | C++, Command Line Arguments, Parsing, Library | Computer & Information Sciences | Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ | Stampede-3: 3.1.1, 3.2.0 | |||||||||
cython | Aces, Faster | Cython is an optimising static compiler for both the Python programming language and the extended Cython programming language (based on Pyrex). It makes writing C extensions for Python as easy as Python itself. Description Source: https://cython.org/ |
Cython is a programming language that makes it easy to write C extensions for Python. It provides a superset of the Python language that allows for calling C functions and declaring C types on variables and class attributes. | Cython allows for easy integration of C libraries and functions with Python code, enabling developers to speed up Python code by writing performance-critical portions in C. It also provides static type declarations that can lead to performance improvements over pure Python code. | https://cython.readthedocs.io/en/latest/ | Language Compiler | Programming Language, C Extensions, Python, Cython | https://cython.org/ | Computer & Information Sciences | https://cython.readthedocs.io/en/latest/src/tutorial/cython_tutorial.html https://pythonprogramming.net/introduction-and-basics-cython-tutorial/ https://www.youtube.com/watch?v=JKCjsRDffXo |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.29.33, 3.0.7 Faster: 0.29.22, 0.29.30, 0.29.33, 3.0A5, 3.0.7 |
Compiler | |||
cython-blis | Aces | Fast BLAS-like operations from Python and Cython, without the tears. This repository provides the Blis linear algebra routines as a self-contained Python C-extension. Description Source: https://github.com/explosion/cython-blis |
Cython wrapper around BLIS linear algebra library for Python. | Provides a Cython interface for the BLIS linear algebra library, allowing for efficient linear algebra computations in Python. BLIS is a high-performance, portable, and thread-safe open-source library for linear algebraic operations. | https://github.com/explosion/cython-blis/blob/master/extra-include/configure | Library | Cython, Blis, Linear Algebra, Python | https://github.com/explosion/cython-blis | Computer & Information Sciences | https://github.com/explosion/cython-blis/tree/master?tab=readme-ov-file#usage | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.9.1 | Computational Software | |||
cytoolz | Faster | CyToolz is a "cythonized" version of the Toolz library, providing high performance utility functions for iterables, functions, and dictionaries in Python. It offers a set of functional tools for iterators that extends the itertools module with additional functions. | - High Performance Utility Functions For Iterables, Functions, & Dictionaries, - Extends The Itertools Module With Additional Functions, - Improved Performance Through Cython Optimization | Utility | Python Library, Functional Programming, Utility Functions | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.9.0-Python-2.7.16, 0.12.0-Python-3.9.6 | Python Library | |||||||
cyvcf2 | Anvil | Cyvcf2 is a cython wrapper around htslib built for fast parsing of Variant Call Format (VCF) files. das_t | CyVCF2 is a fast and efficient Python interface for reading and writing Variant Call Format (VCF) files. It provides a high-level API that simplifies the manipulation and analysis of genetic variants. | 1. Read and write VCF files efficiently.\r 2. Extract genetic variants and associated information.\r 3. Filter variants based on user-defined criteria.\r 4. Perform complex genomic analyses and comparisons.\r 5. Integrate seamlessly with other Python libraries for genomics. |
Library | Genomics | Bioinformatics | Genomics, Vcf, Variant Calling, Python | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/cyvcf2 | Anvil: 0.30.14 | Computational | ||||
dace | Faster | dace (Data Assimilation for Categorical and High-Dimensional Data) is a Python toolkit for data assimilation, specifically designed for high-dimensional and categorical data. It provides a range of data assimilation algorithms and tools to effectively integrate observational data and models to improve predictions and understanding of complex systems. | 1. Support for high-dimensional and categorical data assimilation.\r 2. Implementation of various data assimilation algorithms.\r 3. Integration of observational data with models.\r 4. Improves predictions and understanding of complex systems. |
Data Assimilation, Python Toolkit, Observational Data Integration | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.14.1 | |||||||||
dal | Kyric | DAL is a library for collision avoidance in robotics applications. | Collision Avoidance Algorithms, Robotics Applications | Collision Avoidance Software | Robotics, Collision Avoidance | Engineering & Technology | Kyric: Latest, 2021.1.1 | Library | ||||||||
dalton | Faster | Dalton is an powerful quantum chemistry program for the study of molecular properties. It can perform a variety of high-level ab initio quantum chemical calculations for both ground and excited states. | Some core features of Dalton include molecular property calculations, density functional theory calculations, coupled cluster calculations, symmetry-adapted perturbation theory, and relativistic effects calculations. | Simulation | Theoretical Chemistry | Physical Chemistry | Quantum Chemistry, Molecular Properties, Ab Initio Calculations | Chemical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2020.0 | Quantum Chemistry Software | |||||
darshan-runtime | Expanse | Darshan (runtime) is a scalable HPC I/O characterization tool designed to capture an accurate picture of application I/O behavior, including properties such as patterns of access within files, with minimum overhead. | Darshan is a lightweight I/O characterization tool for high-performance computing (HPC) applications. It allows users to understand and improve the I/O behavior of their applications by collecting I/O access patterns and performance metrics. | 1. I/O access pattern analysis\r 2. Performance metrics collection\r 3. Lightweight and easy-to-use\r 4. Designed for HPC applications |
Tool | High-Performance Computing | Infrastructure & Instrumentation | I/O Characterization, High-Performance Computing, Performance Analysis | Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 3.2.1 | Performance Analysis | ||||
darshan-util | Expanse | Darshan (util) is collection of tools for parsing and summarizing log files produced by Darshan (runtime) instrumentation. This package is typically installed on systems (front-end) where you intend to analyze log files produced by Darshan (runtime). | Darshan is a scalable HPC I/O characterization tool designed to capture I/O behavior in high-performance computing applications. The darshan-util package provides a set of utilities for analyzing and visualizing the I/O data collected by Darshan. | 1. Analyzing I/O behavior in HPC applications\r 2. Visualizing I/O patterns and bottlenecks\r 3. Generating reports for understanding application I/O performance |
Utility | Hpc, I/O Characterization, Data Analysis | Physical Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 3.2.1 | Hpc Tools | ||||||
das_tool | Anvil | DAS Tool is an automated method that integrates the results of a flexible number of binning algorithms to calculate an optimized, non-redundant set of bins from a single assembly. | das_tool is a versatile software tool used for analyzing and visualizing large-scale genomic data in the context of chromatin interactions and 3D genome organization. It provides researchers with a range of functions to explore spatial genome architecture and identify regulatory elements. | Analyze Large-Scale Genomic Datasets, Visualize Chromatin Interactions, Study 3D Genome Organization, Identify Regulatory Elements, Explore Spatial Genome Architecture | Genomic Data Analysis Tool | Genomics | Bioinformatics | Genomics, Chromatin Interactions, Spatial Genome Architecture, Regulatory Elements, Bioinformatics, Data Visualization | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/das_tool | Anvil: 1.1.6 | Analysis & Visualization | ||||
dask | Aces, Faster | Dask makes it easy to scale the Python libraries that you know and love like NumPy, pandas, and scikit-learn. It also allows you to Parallelize any Python code with Dask Futures, letting you scale any function and for loop, and giving you control and power in any situation. Description Source: https://www.dask.org/ |
Dask is a flexible parallel computing library for analytic computing, designed to scale from single machines to large clusters. It provides advanced parallelism for analytics, enabling performance at scale for the tools you love. | Parallel Computing, Scalability, Efficient Task Scheduling, Integration With Existing Libraries Like Numpy, Pandas, & Scikit-Learn | https://docs.dask.org/en/latest/api.html | Library | Parallel Computing, Scalable Computing, Analytics, Data Science | https://www.dask.org/ | Computer & Information Sciences | https://docs.dask.org/en/latest/10-minutes-to-dask.html https://tutorial.dask.org/ https://www.youtube.com/watch?v=mqdglv9GnM8 |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2021.9.1, 2022.1.0, 2022.10.0 Faster: 2.8.0-Python-3.7.4, 2.18.1-Python-3.8.2, 2021.2.0, 2022.1.0, 2022.7.0, 2022.10.0 |
Computational Software | |||
datasets | Anvil | Datasets refer to collections of data that are organized and structured in a specific format for analysis, processing, and sharing. They are used in various research fields to draw insights, build models, and validate theories. | Organized Collections Of Data, Structured Format For Analysis, Support For Processing & Sharing, Used To Draw Insights & Build Models | Data, Research, Analysis, Processing, Sharing | Anvil: https://www.rcac.purdue.edu/software/datasets | Anvil: Datasets | ||||||||||
db | Aces, Faster | Berkeley DB enables the development of custom data management solutions, without the overhead traditionally associated with such custom projects. | db is a simple and minimalistic database library for Python, designed to provide a lightweight interface for basic database operations. | 1. Simple and easy-to-use interface for database operations. 2. Support for common database operations like creating tables, inserting data, querying data, updating records, and deleting records. 3. Lightweight and minimalistic design for quick integration into Python projects. | Library | Database, Python Library | Computer & Information Sciences, Computer Science | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 18.1.40 Faster: 18.1.32, 18.1.40 |
Database Library | ||||||
db_file | Faster | db_file is a software tool designed for managing and manipulating database files. It provides functionalities for creating, modifying, querying, and extracting data from database files. | Create & Manage Database Files, Execute Queries On Database Files, Extract Data From Database Files, Modify & Update Database Files | Tool | Database Management, Data Manipulation, Querying, Data Extraction | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.855, 1.856, 1.858 | Database Management | |||||||
dbcsr | Aces, Faster | DBCSR stands for Distributed Blocked Compressed Sparse Row. DBCSR is a library designed to efficiently perform sparse matrix-matrix multiplication, among other operations. | dbcsr (distributed block compressed sparse row) is a library for creating distributed block-sparse matrix data structures and performing operations on them efficiently. It is designed for high-performance computing (HPC) applications that involve large, sparse matrices. | 1. Creation of distributed block-sparse matrix data structures\r 2. Efficient operations on block-sparse matrices\r 3. Designed for high-performance computing (HPC) applications\r 4. Supports parallel computation\r 5. Optimized for large, sparse matrices |
Library | Hpc, Sparse Matrices, Parallel Computing | Other Natural Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.5.0, 2.6.0 Faster: 2.5.0 |
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dbd-mysql | Faster | DBD::mysql is the Perl5 Database Interface driver for the MySQL database. In other words, DBD::mysql is an interface between the Perl programming language and the MySQL programming API that comes with the MySQL relational database management system. | 1. Allows Perl scripts to connect to a MySQL database.\r 2. Provides a set of functions for database management, querying, and manipulation.\r 3. Supports efficient integration of MySQL database functionality within Perl applications. |
Software Library | Database, Mysql | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 4.050-Perl-5.30.0 | Database Interface Driver | |||||||
dbg2olc | Anvil | Dbg2olc is used for efficient assembly of large genomes using long erroneous reads of the third generation sequencing technologies. | dbg2olc is a tool developed for genome assembly using a de Bruijn graph based on overlap-layout-consensus (OLC) algorithm. It aims to efficiently assemble large and complex genomes by utilizing both long and short reads. | De Bruijn Graph Assembly, Overlap-Layout-Consensus Algorithm, Hybrid Assembly Using Long & Short Reads, Efficient Assembly Of Large & Complex Genomes | Genome Assembly Software | Genome Assembly | Bioinformatics | Genome Assembly, De Bruijn Graph, Olc Algorithm, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/dbg2olc | Anvil: 20180222, 20200723 | Bioinformatics Tool | ||||
dbus | Aces, Faster | D-Bus is a message bus system, a simple way for applications to talk to one another. In addition to interprocess communication, D-Bus helps coordinate process lifecycle; it makes it simple and reliable to code a "single instance" application or daemon, and to launch applications and daemons on demand when their services are needed. Description Source: https://www.freedesktop.org/wiki/Software/dbus/ |
D-Bus is a message bus system, a simple way for applications to talk to one another. In addition to interprocess communication, D-Bus helps coordinate process lifecycle management. | 1. Interprocess communication between applications. 2. Coordination of process lifecycle management. 3. Suitable for use in both small and large systems. 4. Enables communication between applications written in different programming languages. | https://dbus.freedesktop.org/doc/dbus-specification.html | Middleware | Message Bus System, Interprocess Communication, Process Lifecycle Management | https://www.freedesktop.org/wiki/Software/dbus/ | Computer & Information Sciences | https://dbus.freedesktop.org/doc/dbus-tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.13.18, 1.14.0, 1.15.2, 1.15.4 Faster: 1.13.12, 1.13.18, 1.14.0, 1.15.2, 1.15.4 |
System Software | |||
dbus-glib | Aces, Faster | D-Bus is a message bus system, a simple way for applications to talk to one another. | D-Bus is a message bus system for inter-application communication and coordination. dbus-glib is a library for GLib based applications to communicate with D-Bus. | dbus-glib provides a high-level API for interacting with D-Bus, allowing applications to publish objects and call methods on remote objects over the D-Bus. | Api | D-Bus, Inter-Process Communication, Glib | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.112 Faster: 0.112 |
Library | ||||||
dcmtk | Aces, Faster | DCMTK is a collection of libraries and applications implementing large parts the DICOM standard. It includes software for examining, constructing and converting DICOM image files, handling storage media, sending and receiving images over a network connection, as well as demonstrative image storage and worklist servers. Description Source: https://dicom.offis.de/dcmtk/ |
DCMTK is a collection of libraries and applications implementing large parts the DICOM standard. It includes software for examining, constructing and converting DICOM image files, handling offline media, sending and receiving images over a network connection, as well as demonstrative image processing, and pattern recognition techniques. | DICOM image file examination, construction, and conversion; Handling offline media; Sending and receiving images over a network connection; Demonstrative image processing; Pattern recognition techniques. | https://support.dcmtk.org/docs/ | Data Processing & Analysis | Medical Biotechnology | Medical & Health Sciences | Dicom, Medical Imaging, Healthcare, Image Processing | https://dicom.offis.de/dcmtk/ | Medical & Health Sciences | https://support.dcmtk.org/redmine/projects/dcmtk/wiki/Howto | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.6.7 Faster: 3.6.7 |
Library & Applications | |
ddt | Bridges-2, Stampede3 | Linaro DDT is the number one server and HPC debugger in research, industry, and academia for software engineers and scientists developing C++, C, Fortran parallel and threaded applications on CPUs, GPUs, Intel and Arm. Linaro DDT is the trusted debugging tool for ensuring program correctness for applications ranging from single process to exascale. Description Source: https://www.linaroforge.com/linaroDdt/ |
DDT is a powerful, flexible, scalable, and easy-to-use debugging and performance analysis tool for parallel and serial codes. | DDT offers intuitive graphical user interface, multi-language support for C, C++, and Fortran, advanced debugging capabilities, memory debugging, parallel debugging for MPI, OpenMP, and hybrid codes, performance analysis for identifying bottlenecks, debugging in a distributed environment, and efficient visualization of program behavior. | https://docs.linaroforge.com/23.1.1/html/forge/ddt/index.html | Debugger | Debugging Tool, Performance Analysis, Parallel Computing, Serial Computing | https://www.linaroforge.com/linaroDdt/ | Computer & Information Sciences | https://docs.linaroforge.com/23.0.3/html/forge/worked_examples_appendix/mmult/index.html# https://docs.linaroforge.com/23.0.3/html/forge/general_troubleshooting_appendix/index.html |
Bridges-2: https://www.psc.edu/resources/software/ddt Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Bridges-2: 20.1.3, 20.2.1, 23.0.3 Stampede-3: 23.1.2 |
Development Tool | |||
dealii | Bridges-2 | deal.II — a name that originally meant to indicate that it is the successor to the Differential Equations Analysis Library — is a C++ program library targeted at the computational solution of partial differential equations using adaptive finite elements. It uses state-of-the-art programming techniques to offer you a modern interface to the complex data structures and algorithms required. Description Source: https://www.dealii.org/about.html |
https://www.dealii.org/current/doxygen/deal.II/index.html | Library | https://www.dealii.org/ | https://www.dealii.org/developer/doxygen/deal.II/step_1.html https://www.dealii.org/developer/doxygen/deal.II/step_2.html |
Bridges-2: https://www.psc.edu/resources/software/dealii | Bridges-2: 9.2.0, 9.3.1 Stampede-3: 9.5.2 |
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debreak | Anvil | Debreak is a SV caller for long-read single-molecular sequencing data. decons | debreak is a tool for analyzing and visualizing the output generated by the debarcoder software. Debarcoder is used for decoding high-throughput sequencing data from combinatorial CRISPR screens. | debreak allows users to easily interpret the results of debarcoder by providing visualization and statistical analysis tools. It helps in understanding the performance of the CRISPR screen and identifying significant hits. | Bioinformatics Tool | Bioinformatics, Hpc Tools | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/debreak | Anvil: 1.3 | Analysis Tool | ||||||
debugger | Kyric | A debugger is a software tool that allows programmers to track down and fix bugs (errors) in their programs. It enables users to step through code, inspect variables, set breakpoints, and analyze the program's execution flow. | Stepping Through Code, Inspecting Variables, Setting Breakpoints, Analyzing Program Execution Flow | Debugger | Debugging, Software Development | Engineering & Technology | Kyric: Latest, 10.0.0 | Development Tools | ||||||||
decona | Faster | Decona is a Conda package management tool that simplifies the installation and management of software packages, dependencies, and environments through the Conda package manager. | Decona provides a user-friendly interface for creating, managing, and sharing Conda environments. It enables users to easily install, update, and remove Conda packages, as well as manage dependencies and virtual environments. | Conda Package Manager | Conda, Package Management, Software Installation, Dependency Management | Other Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.1.2-Python-3.7.4 | Package Management Tool | |||||||
deconseq | Anvil | DeconSeq: DECONtamination of SEQuence data using a modified version of BWA-SW. | DeconSeq is a novel program specifically designed to automatically decontaminate sequences and detect possible contamination in sequence datasets. It efficiently detects and removes sequence contamination from high-throughput sequencing reads. The tool is particularly useful in metagenomics studies to ensure the quality and accuracy of the analysis results. | 1. Removal of contaminating sequences from datasets\r 2. Detection of contamination based on user-defined criteria\r 3. Support for various sequence formats\r 4. Customizable parameters for tailored analysis\r 5. Efficient processing of high-throughput sequencing data |
Analysis Tool | Bioinformatics, Sequence Analysis, Metagenomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/deconseq | Anvil: 0.4.3 | Bioinformatics Tool | ||||||
deepbgc | Anvil | Deepbgc is a tool for BGC detection and classification using deep learning. | DeepBGC is a tool for the detection and classification of biosynthetic gene clusters in microbial genomes using deep learning techniques. It focuses on identifying gene clusters responsible for the production of specialized metabolites. | 1. Detection of biosynthetic gene clusters (BGCs) in microbial genomes. 2. Classification of BGCs based on the type of specialized metabolites they produce. 3. Utilizes deep learning algorithms for improved accuracy in BGC prediction. 4. Allows for the exploration and visualization of identified BGCs. | Bioinformatics Tool | Bioinformatics | Biological Sciences | Biosynthetic Gene Clusters, Microbial Genomes, Deep Learning, Metabolites | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/deepbgc | Anvil: 0.1.26, 0.1.30 | Computational Tool | ||||
deepconsensus | Anvil | DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data. | DeepConsensus is a tool for variant calling in MinION nanopore sequencing data. It uses deep learning to increase accuracy and sensitivity in detecting single nucleotide variants (SNVs) and insertion/deletion (indel) mutations. | 1. Variant calling in MinION nanopore sequencing data\r 2. Utilizes deep learning for improved accuracy and sensitivity\r 3. Detection of single nucleotide variants (SNVs) and insertion/deletion (indel) mutations |
Tool | Variant Calling, Minion Nanopore Sequencing, Deep Learning | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/deepconsensus | Anvil: 0.2.0 | Bioinformatics | ||||||
deepdiff | Aces | DeepDiff is a Python library that provides comprehensive and detailed diffing capabilities, allowing for the deep comparison of data structures within Python. It is capable of identifying differences between dictionaries, lists, sets, and other complex data types, making it highly useful for tasks that require detailed tracking of changes or discrepancies in data over time, such as data analysis, testing, and debugging. | DeepDiff is a Python library for deep (nested) comparisons of objects. | 1. Deep comparison of dictionaries, lists, sets, and strings\r 2. Visualization of the differences between two objects\r 3. Ability to ignore specific keys or paths during comparison\r 4. Customizable comparison options and formatting |
https://zepworks.com/deepdiff/current/diff.html | Python Library | Python Library, Data Comparison, Object Comparison | https://github.com/seperman/deepdiff | Computer & Information Sciences | https://zepworks.com/posts/deepdiff-tutorial-compare-numbers/ | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 5.8.1, 6.7.1 | Library | |||
deepsignal2 | Anvil | Deepsignal2 is a deep-learning method for detecting DNA methylation state from Oxford Nanopore sequencing reads. | Deepsignal2 is a deep learning-based toolkit for nanopore signal processing and variant detection. It is designed to accurately detect DNA modifications and structural variants from raw nanopore sequencing data. | 1. Process raw nanopore signal data\r 2. Detect DNA modifications and structural variations\r 3. Utilizes deep learning algorithms for improved accuracy\r 4. Supports real-time analysis of nanopore sequencing data |
Toolkit | Genomics | Genetics | Nanopore Sequencing, Deep Learning, Signal Processing, Variant Detection | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/deepsignal2 | Anvil: 0.1.2 | Bioinformatics | ||||
deeptools | Anvil | deepTools is a suite of python tools particularly developed for the efficient analysis of high-throughput sequencing data, such as ChIP-seq, RNA-seq or MNase-seq. Description Source: https://deeptools.readthedocs.io/en/latest/ |
DeepTools is a suite of tools for the analysis of high-throughput sequencing data, with a focus on ChIP-seq and ATAC-seq data. It provides various functions for quality control, normalization, visualization, and downstream analysis of sequencing data. | Quality Control Of Sequencing Data, Normalization Of Chip-Seq & Atac-Seq Data, Visualization Of Genomic Data, Statistical Analysis Of High-Throughput Sequencing Data | https://deeptools.readthedocs.io/en/latest/content/api.html | Analysis Tool | Genomics | Biology | Bioinformatics, Hpc Tools, Computational Software | https://github.com/deeptools/deepTools | Biological Sciences | https://deeptools.readthedocs.io/en/latest/content/list_of_tools.html https://deeptools.readthedocs.io/en/develop/content/example_usage.html |
Anvil: https://www.rcac.purdue.edu/software/deeptools | Anvil: 3.5.1-Py | Bioinformatics | |
deepvariant | Anvil | DeepVariant is a deep learning-based variant caller that takes aligned reads (in BAM or CRAM format), produces pileup image tensors from them, classifies each tensor using a convolutional neural network, and finally reports the results in a standard VCF or gVCF file. | DeepVariant is a deep learning-based variant caller developed by Google Brain that accurately identifies genetic variants from next-generation DNA sequencing data. | 1. Utilizes deep neural networks for variant calling\r 2. Provides accurate and reliable variant identification\r 3. Supports germline and somatic variant calling\r 4. Optimized for identifying small variants like single nucleotide polymorphisms (SNPs) and insertions/deletions (indels)\r 5. Employs a peer-reviewed, open-source methodology for variant calling |
Variant Caller | Bioinformatics | Genomics | Variant Calling, Genetic Variants, Deep Learning, DNA Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/deepvariant | Anvil: 1.0.0, 1.1.0 | Genomics | ||||
default | Delta | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: Default | |||||||||||||
default-environment | Expanse | Loads default environment modules for this cluster | The default-environment is a basic system setup that provides essential tools and configurations for software development and computational work. It serves as a starting point for creating custom environments tailored to specific requirements and preferences. | Includes Popular Programming Languages Such As Python, C++, Java, & Others, Common Utilities Like Text Editors, Version Control Systems, & Package Managers Are Pre-Installed, Support For Compiling Code, Managing Dependencies, & Running Basic Scripts, Can Be Easily Extended & Customized With Additional Software Packages & Libraries | Default Environment | Development-Environment, Computational-Tools, Software-Utilities | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Default-Environment | Environment Setup | |||||||
default-s11 | Delta | Default-S11 is a high-performance computational software designed for bioinformatics analysis and molecular dynamics simulations. | The software offers advanced tools for sequence alignment, protein structure prediction, molecular docking, and molecular dynamics simulations. It provides multiple algorithms for analyzing biological sequences and predicting protein structures. Default-S11 also includes visualization capabilities for molecular dynamics simulations. | Bioinformatics Tool | Bioinformatics | Biological Sciences | Computational Software, Bioinformatics, Molecular Dynamics, Sequence Analysis, Protein Structure Prediction | Biological Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: Default-S11 | Computational Software | |||||
defaultmodules | Expanse | Default modules are predefined software packages or libraries that are included with the installation of a particular software, compiler, or programming environment. These modules typically consist of commonly used tools or libraries that are essential for various tasks within the software ecosystem. | Predefined Software Packages Or Libraries Included With Software Installations, Essential Tools For Various Tasks Within The Software Ecosystem | Libraries/Modules | Not Applicable | Not Applicable | Software Libraries, Software Packages, Default Modules | Other | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Defaultmodules | Development Tools | |||||
delly | Anvil | Delly is an integrated structural variant (SV) prediction method that can discover, genotype and visualize deletions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read massively parallel sequencing data. | Delly is a structural variant discovery tool that integrates multiple SV detection methods to accurately identify deletions, inversions, duplications, and translocations. | 1. Integrates multiple SV detection methods\r 2. Identifies deletions, inversions, duplications, and translocations\r 3. Provides high accuracy in SV discovery\r 4. Offers visualization tools for easy interpretation of results |
Tool | Structural Variant Discovery | Genomics | Structural Variant Discovery, Sv Detection, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/delly | Anvil: 0.9.1, 1.0.3, 1.1.3, 1.1.5, 1.1.6 | Bioinformatics | ||||
dendropy | Anvil, Faster | DendroPy is a Python library for phylogenetic computing. | DendroPy is a flexible and modular phylogenetic computing library in Python, offering reading, writing, simulation, and manipulation of phylogenetic trees and associated data. | Read & Write Phylogenetic Tree Files In Various Formats, Perform Tree Manipulations, Transformations, & Calculations, Simulate Trees Under A Variety Of Models & Conditions, Analyze & Visualize Phylogenetic Data, Supports A Wide Range Of Phylogenetic Analysis Tools & Methods | Computational | Evolutionary Biology | Biological Sciences | Phylogenetics, Computational Biology, Python Library, Bioinformatics, Phylogenetic Trees | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/dendropy Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 4.5.2 Faster: 4.5.2 |
Library | ||||
desmond | Bridges-2, Faster | Desmond is a molecular dynamics simulation software designed for studying biological systems at the atomic level. It is widely used for drug discovery, protein folding, and molecular interactions. | Molecular Dynamics Simulations, Protein-Ligand Interactions, Free Energy Calculations, Structural Refinement | Molecular Dynamics Software | Structural Biology | Biochemistry & Molecular Biology | Molecular Dynamics, Biological Systems, Drug Discovery, Protein Folding | Biological Sciences | Bridges-2: https://www.psc.edu/resources/software/desmond Faster: https://hprc.tamu.edu/software/faster/ |
Bridges-2: 2020.4 Faster: 2020-1, 2021-1 |
Simulation Software | |||||
dev-utilities | Kyric | Dev-utilities is a collection of various development utilities that assist software developers in various aspects of the development process. These utilities can range from code editors and version control systems to build automation tools and testing frameworks. | Code editors, version control systems, build automation tools, testing frameworks, debugging tools, package managers, linters, code formatters, code generators, documentation generators, continuous integration/delivery tools. | Tools | Development, Utilities | Computer & Information Sciences, Other Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Development Tools | ||||||||
devito | Faster | Devito is a high-level finite difference compiler for solving partial differential equations (PDEs). It generates and optimizes finite difference kernels to achieve high performance on modern computer architectures. | High-Level Symbolic Problem Definition, Automatic Optimization Of Finite Difference Kernels, Geared Towards Seismic Imaging & Inversion, Supports A Range Of Pde Problems | Compiler | Seismic Imaging, Inverse Problems | Numerical Analysis | Finite Difference Compiler, Pde Solver, Computational Science | Applied Mathematics | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 4.6.1-Python-3.8.2 | Computational Science, Optimization | |||||
dft-d3 | Faster | DFT-D3 is a widely used dispersion correction method for density functional theory (DFT) calculations to accurately account for long-range dispersive interactions in molecular systems. It improves the description of non-bonded interactions, including van der Waals forces, and enhances the accuracy of DFT calculations. | 1. Dispersion correction method for DFT calculations.\r 2. Accounts for long-range dispersive interactions.\r 3. Improves description of non-bonded interactions and van der Waals forces.\r 4. Enhances the accuracy of DFT calculations in molecular systems. |
Library | Chemical Sciences | Physical Sciences | Computational Chemistry, Density Functional Theory, Quantum Mechanics | Chemical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.2.0 | Computational Software | |||||
dftbplus | Expanse | DFTB+ is an implementation of the Density Functional based Tight Binding (DFTB) method, containing many extensions to the original method. | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 19.1-Openblas | ||||||||||||
diamond | Anvil, Expanse, Faster | Diamond is sequence aligner for protein and translated DNA searches, designed for high performance analysis of big sequence data. | Diamond is a sequence aligner for protein and translated DNA searches, designed for high performance analysis of protein sequence data utilizing the Diamond heuristic aligner. It is particularly optimized for aligning sequencing reads produced by next-generation sequencing (NGS) machines. | High-Performance Sequence Aligner For Protein & Translated DNA Searches, Optimized For Aligning Data From Ngs Machines, Utilizes The Diamond Heuristic Aligner For Rapid Alignment, Supports Sensitive Alignment Of Multiple Query Sequences Against A Large Sequence Database, Provides Significant Speedup Compared To Blast Tools | Bioinformatics Tool | Genomics, Proteomics | Bioinformatics | Sequence Alignment, Ngs Analysis, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/diamond Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 2.0.13, 2.0.14, 2.0.15, 2.1.6 Expanse: 0.9.25 Faster: 2.0.13, 2.1.0 |
Sequence Aligner | ||||
diffutils | Kyric | Diffutils is a collection of utilities for comparing and finding differences between text files. It includes programs like `diff` for showing the differences between two files, `cmp` for comparing two files byte by byte, and `diff3` for comparing three files. | 1. Generating line-by-line differences between text files.\r 2. Showing changes between files in a user-friendly format.\r 3. Comparing files at byte level with detailed output.\r 4. Merging changes from multiple versions of a file. |
https://www.gnu.org/software/diffutils/manual/diffutils.html | Text Processing | Text Comparison, File Difference, Text Analysis, Version Control | https://www.gnu.org/software/diffutils/ | Engineering & Technology | https://www.gnu.org/software/diffutils/manual/html_node/Invoking-diff.html#Invoking-diff | Utility | ||||||
dill | Aces, Faster | dill extends Python’s pickle module for serializing and de-serializing Python objects to the majority of the built-in Python types. Description Source: https://dill.readthedocs.io/en/latest/ |
Dill is a serialization library for Python datastructures. It provides the ability to serialize all standard Python data types without needing to be pre-informed about their existence, offering extended functionality beyond what is available in the standard `pickle` library. | 1. Supports the serialization of almost all Python data types.\r 2. Can serialize functions and classes.\r 3. Supports lambda functions.\r 4. Provides a mechanism to serialize instances of un-picklable classes.\r 5. Allows for easy storage and retrieval of Python objects. |
https://dill.readthedocs.io/en/latest/ | Library | Serialization, Python, Datastructures, Library | https://pypi.org/project/dill/ | Computer & Information Sciences | https://dill.readthedocs.io/en/latest/#basic-usage https://github.com/uqfoundation/dill?tab=readme-ov-file#more-information |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.3.4, 0.3.6, 0.3.7 Faster: 0.3.4, 0.3.6, 0.3.7 |
Serialization Library | |||
dimemas | Kyric | DIMemas is a software tool for the automatic performance prediction of parallel applications. It utilizes simulation techniques to estimate the performance of parallel applications on large-scale systems. | Automatic Performance Prediction, Simulation Techniques, Estimation Of Parallel Application Performance On Large-Scale Systems | https://github.com/bsc-performance-tools/dimemas/blob/master/cfgs/ideal.cfg | Performance Prediction Tool | Performance Prediction, Parallel Applications, Simulation, Large-Scale Systems | https://tools.bsc.es/dimemas | Engineering & Technology | https://tools.bsc.es/doc/introduction_dimemas.pdf https://tools.bsc.es/sites/default/files/documentation/slides/Dimemas-Hands-On.pdf |
Kyric: 5.4.2 | Simulation Tool | |||||
dlib | Faster | dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in a wide range of applications including computer vision, face detection, object detection, facial landmarks, pose estimation, and more. | Machine Learning Algorithms, Computer Vision, Face Detection, Object Detection, Facial Landmarks, Pose Estimation | Library | Machine Learning, Computer Vision, Object Detection, Facial Recognition, Pose Estimation | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 19.22-Cuda-11.3.1 | Toolkit | |||||||
dm-reverb | Faster | dm-reverb is a Python library for efficient data loading and storage in deep learning and machine learning projects, particularly designed for use with TensorFlow. It provides a simple and flexible API for managing large datasets by storing data on disk and loading it into memory in a suitable format for training models. | Efficient Data Loading & Storage, Designed For Deep Learning & Machine Learning Projects, Flexible Api, Supports Storing Data On Disk, Suitable For Use With Tensorflow | Python Library | Python Library, Data Loading, Data Storage, Machine Learning, Deep Learning | Computer Science | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.2.0 | Library | |||||||
dm-tree | Aces, Faster | dm-tree is a python library for working with nested data structures. In a way, tree generalizes the builtin map function which only supports flat sequences, and allows to apply a function to each "leaf" preserving the overall structure. Description Source: https://github.com/google-deepmind/tree |
dm-tree is a Python library for manipulating nested tree-like data structures with ease and efficiency. It provides a comprehensive set of tools for working with hierarchical data in a user-friendly manner. | Efficient Manipulation Of Tree Structures, Support For Nested & Hierarchical Data, Traversal & Querying Capabilities, Serialization & Deserialization Of Tree Data | https://tree.readthedocs.io/en/latest/api.html | Library | Python Library, Hierarchical Data, Tree Structures, Data Manipulation | https://github.com/google-deepmind/tree | Computer & Information Sciences | https://tree.readthedocs.io/en/latest/recipes.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.1.6, 0.1.8 Faster: 0.1.5, 0.1.6, 0.1.8 |
Scientific Computing | |||
dnaapler | Anvil | dnaapler is a simple python program that takes a single nucleotide input sequence (in FASTA format), finds the desired start gene using blastx against an amino acid sequence database, checks that the start codon of this gene is found, and if so, then reorients the chromosome to begin with this gene on the forward strand. | dnaapler is a bioinformatics tool for predicting DNA replication origins in microbial genomes. It uses machine learning models trained on replication initiation sites to identify potential origins of replication. | 1. Prediction of DNA replication origins\r 2. Machine learning-based approach\r 3. Identification of replication initiation sites in microbial genomes |
Prediction Tool | Bioinformatics | Genomics | Bioinformatics, Tool, DNA Replication, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/dnaapler | Anvil: 0.1.0 | Bioinformatics Tool | ||||
dnaio | Anvil | Dnaio is a Python 3.7+ library for very efficient parsing and writing of FASTQ and also FASTA files. | dnaio is a Python library for reading and writing DNA sequences efficiently. It provides high-performance I/O operations for DNA sequence data, allowing for seamless integration into bioinformatics workflows. | Efficient Reading & Writing Of DNA Sequences, Compatibility With Various Sequence File Formats, Optimized For High Performance, Integration With Bioinformatics Pipelines | Python Library | Genetics | Bioinformatics | Python Library, Bioinformatics, DNA Sequences, Sequence Data | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/dnaio | Anvil: 0.8.1 | Library | ||||
dnnl | Kyric | Deep Neural Network Library (DNNL) is an open-source, performance-oriented library for deep learning applications. Formerly known as Intel Math Kernel Library for Deep Neural Networks (MKL-DNN), it provides optimized building blocks for implementation of deep learning neural network layers on various hardware platforms. | 1. Efficient deep learning neural network layer implementations. 2. Open-source and highly optimized for performance. 3. Support for various hardware platforms. 4. Integration with popular deep learning frameworks like TensorFlow and PyTorch. | https://oneapi-src.github.io/oneDNN/ | Deep Learning Library | Deep Learning | Artificial Intelligence & Intelligent Systems | Deep Learning, Neural Networks, Machine Learning, Performance Optimization | https://github.com/oneapi-src/oneDNN | Computer & Information Sciences | https://oneapi-src.github.io/oneDNN/dev_guide_examples.html | Kyric: Latest, 2021.1.1 | Library | |||
dnnl-cpu-gomp | Kyric | The dnnl-cpu-gomp is an open-source deep neural network library developed for CPU-based computations employing OpenMP (Open Multi-Processing) as a thread-processing technology. | Optimized For Deep Neural Network Computations On Cpus, Utilizes Openmp For Parallelism In Thread Processing, Includes Various Functions & Operations For Neural Network Implementations, Supports Efficient Execution Of Deep Learning Models On Cpu Architectures | https://oneapi-src.github.io/oneDNN/ | Computational Software | Deep Learning, Neural Networks, Openmp, Cpu Computing | https://github.com/oneapi-src/oneDNN | Computer & Information Sciences | https://oneapi-src.github.io/oneDNN/dev_guide_examples.html | Kyric: Latest, 2021.1.1 | Libraries & Frameworks | |||||
dnnl-cpu-iomp | Kyric | dnnl-cpu-iomp is an optimization library for deep neural network computations on CPU using Intel OpenMP (iomp) for improved performance. | 1. Accelerates deep learning inferencing on CPU.\r 2. Utilizes Intel OpenMP for parallel processing.\r 3. Optimized for performance with deep neural network computations on Intel CPUs. |
https://oneapi-src.github.io/oneDNN/ | Deep Learning, Optimization, Cpu Acceleration | https://github.com/oneapi-src/oneDNN | Computer & Information Sciences | https://oneapi-src.github.io/oneDNN/dev_guide_examples.html | Kyric: Latest, 2021.1.1 | Intel Ai/Ml | ||||||
dnnl-cpu-tbb | Kyric | https://oneapi-src.github.io/oneDNN/ | https://github.com/oneapi-src/oneDNN | https://oneapi-src.github.io/oneDNN/dev_guide_examples.html | Kyric: Latest, 2021.1.1 | Intel Ai/Ml | ||||||||||
docker | Expanse | Docker is a platform that enables users to develop, ship, and run applications within containers. Containers allow developers to package up an application with all parts it needs, such as libraries and other dependencies, and ship it all out as one package. | Containerization Of Applications, Efficient & Lightweight, Portability Across Environments, Automated Deployment, Scalability, Isolation Of Applications | Virtualization | Containerization, Deployment, Scalability, Isolation | Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 20.10.21 | Containerization Platform | |||||||
docker-user | Aces | Rootless mode allows running the Docker daemon and containers as a non-root user to mitigate potential vulnerabilities in the daemon and the container runtime. Rootless mode executes the Docker daemon and containers inside a user namespace. To start the daemon: 'dockerd-rootless-setuptool.sh install --skip-iptables'. To test it: 'docker run hello-world'. To stop the daemon: 'dockerd-rootless-setuptool.sh uninstall --skip-iptables' | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 202311 | ||||||||||||
dorado | Aces | Dorado is a high-performance, easy-to-use, open source basecaller for Oxford Nanopore reads. Description Source: https://github.com/nanoporetech/dorado |
Dorado is a software tool used for performance evaluation and benchmarking in HPC (High-Performance Computing) environments. It allows users to assess the performance of parallel applications and optimize their running times on supercomputers and clusters. | Dorado provides capabilities for analyzing parallel application performance, identifying bottlenecks, measuring scalability, and optimizing code efficiency. It offers detailed performance metrics and visualizations to help users understand the behavior of their applications on parallel architectures. | https://dorado.readthedocs.io/en/latest/dorado/index.html#reference-api | Tool | Sciences | Biology | Performance Evaluation, Benchmarking, Hpc, Supercomputing | https://github.com/nanoporetech/dorado | Engineering & Technology | https://dorado.readthedocs.io/en/latest/dorado/index.html#getting-started-with-dorado https://dorado.readthedocs.io/en/latest/dorado/core.html |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.5.2-Cuda-11.8.0 Bridges-2: 0.6.0 |
Software | |
dos2unix | Delta | dos2unix converts text files with DOS or Mac line breaks to Unix line breaks and vice versa. Description Source: https://dos2unix.sourceforge.io/#DOS2UNIX |
dos2unix is a command-line utility that converts text files with DOS or Windows line endings (CRLF) to Unix line endings (LF) format. | 1. Converts text files from DOS/Windows line endings (CRLF) to Unix line endings (LF).\r 2. Preserves the file ownership, permissions, and timestamps.\r 3. Can handle conversion of multiple files in batch mode. |
https://waterlan.home.xs4all.nl/dos2unix/man1/dos2unix.htm | Utility | Text Conversion, Line Endings, Command-Line Utility | https://waterlan.home.xs4all.nl/dos2unix.html | Computer & Information Sciences | https://waterlan.home.xs4all.nl/dos2unix/man1/dos2unix.htm#EXAMPLES | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 7.4.4 | Data Management | |||
dot | Ookami | Graphviz is open source graph visualization software. It has several main graph layout programs. It also has web and interactive graphical interfaces, and auxiliary tools, libraries, and language bindings. | Graph layout programs, web and interactive graphical interfaces, auxiliary tools, libraries, language bindings | Graph Visualization Software | Graph Visualization, Open Source, Graph Layout | Computer & Information Sciences | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: Dot | Visualization Tool | |||||||
double-conversion | Aces, Faster | Double-Conversion provides binary-decimal and decimal-binary routines for IEEE doubles. This library consists of efficient conversion routines that have been extracted from the V8 JavaScript engine. Description Source: https://github.com/google/double-conversion |
double-conversion is a performant library for converting double-precision floating-point values to and from decimal strings, designed for high-performance and precision in conversions. | 1. Efficient conversion of double-precision floating-point numbers.\r 2. High precision in decimal string conversion.\r 3. Optimized for performance.\r 4. Supports both converting double to string and parsing strings into doubles. |
https://github.com/google/double-conversion/blob/master/double-conversion/string-to-double.h | Library | Conversion, Performance, Precision | https://github.com/google/double-conversion | Computer & Information Sciences | https://github.com/google/double-conversion/blob/master/test/cctest/test-conversions.cc | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.1.5, 3.2.0, 3.2.1, 3.3.0 Faster: 3.1.4, 3.1.5, 3.2.0, 3.2.1, 3.3.0 |
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doxygen | Aces, Expanse, Faster, Ookami | Doxygen is a widely-used documentation generator tool in software development. It automates the generation of documentation from source code comments, parsing information about classes, functions, and variables to produce output in formats like HTML and PDF. Description Source: https://www.doxygen.nl/ |
Doxygen is a documentation generator tool that is used to generate software reference documentation from annotated source code. It supports multiple programming languages and produces output in various formats, including HTML, LaTeX, RTF, and more. | Automatic Generation Of Documentation From Source Code, Support For Multiple Programming Languages Including C++, Objective-C, C#, Java, Python, Etc., Output Documentation In Various Formats Such As Html, Latex, Rtf, Xml, & Man Pages, Support For Code Cross-Referencing, Inheritance Diagrams, Collaboration Diagrams, & More | https://www.doxygen.nl/manual/index.html | Tool | Documentation Generator, Software Development, Programming | https://www.doxygen.nl/ | Software Engineering, Systems, & Development | https://www.doxygen.nl/manual/starting.html https://www.doxygen.nl/manual/doxygen_usage.html https://www.youtube.com/watch?v=LZ5E4vEhsKs |
Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 1.8.20, 1.9.1, 1.9.4, 1.9.5, 1.9.7, 1.9.8 Expanse: 1.8.17 Faster: 1.8.14, 1.8.16, 1.8.17, 1.8.20, 1.9.1, 1.9.4, 1.9.5, 1.9.7, 1.9.8 Ookami: 1.9.5 |
Documentation Generation | |||
dpct | Kyric | Data Parallel C++ for CUDA is a C++ programming model for accelerators based on the NVIDIA CUDA architecture. It allows users to write C++ code that can be compiled to target NVIDIA GPUs using CUDA for parallel execution. | Supports C++ programming model for NVIDIA GPUs, enables users to write C++ code for parallel execution on GPUs, allows compilation of C++ code to target CUDA architecture, provides accelerated computing capabilities. | https://github.com/ilastik/dpct/blob/main/README.md | Development Compiler | Cuda Programming, Gpu Computing, Parallel Programming | https://github.com/ilastik/dpct/ | Computer & Information Sciences | https://github.com/ilastik/dpct/blob/main/test/test.py | Kyric: Latest, 2021.1.1 | Compiler | |||||
dpl | Kyric | dpl is a software for performing direct programming language analysis. | It provides tools for analyzing the structure and syntax of programming languages directly. | https://www.rubydoc.info/github/travis-ci/dpl | Programming Language Analysis, Syntax Analysis, Language Structure Analysis | https://github.com/travis-ci/dpl | https://www.rubydoc.info/github/travis-ci/dpl/Dpl/Examples#cmds-instance_method | Kyric: Latest, 2021.1.1 | ||||||||
draco | Aces, Faster | Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics. | Draco is a software library for compressing and decompressing 3D geometric meshes and point clouds. It is designed to improve the storage and transmission of 3D graphics data by offering high compression ratios while maintaining the geometric integrity of the data. | 1. High compression ratios for 3D geometric data\r 2. Maintains geometric integrity during compression and decompression\r 3. Supports both mesh and point cloud data formats\r 4. Optimized for performance and memory usage\r 5. Portable and easy to integrate into existing software pipelines |
Library | Compression, 3D Graphics, Geometric Data, Mesh, Point Cloud | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.5.6 Faster: 1.5.6 |
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dragonflye | Anvil | Dragonflye is a pipeline that aims to make assembling Oxford Nanopore reads quick and easy. drep: drep/3.2 | Dragonflye is a computational software package designed for the analysis and visualization of biological networks and pathways. It offers tools for studying the interactions between genes, proteins, and other biological molecules to gain insights into complex biological processes. | Some of the core features of Dragonflye include network visualization, pathway analysis, gene expression data integration, network clustering, and network motif identification. It allows users to explore and analyze large-scale biological networks to identify key regulatory elements and functional modules. | Computational Software | Systems Biology | Bioinformatics | Biology, Network Analysis, Pathway Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/dragonflye | Anvil: 1.0.13, 1.0.14 | Analysis & Visualization Tools | ||||
drep | Anvil | Drep is a python program for rapidly comparing large numbers of genomes. | drep (Dereplicator) is a tool for fast and accurate dereplication of genomes in microbial datasets. It helps to identify and remove duplicate sequences to ensure that downstream analyses are not biased by redundant data. | Dereplication Of Microbial Genomes, Identification & Removal Of Duplicate Sequences, Improving Efficiency & Accuracy Of Downstream Analyses | Bioinformatics | Microbiome, Genome Analysis, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/drep | Anvil: 3.2.2 | Algorithm/Tool | ||||||
drop-seq | Anvil | Drop-seq are java tools for analyzing Drop-seq data. | Drop-seq is a computational method that enables biologists to analyze the gene expression profiles of thousands of individual cells in a single experiment. It is designed to perform single-cell RNA sequencing using microfluidic techniques. | 1. Enables analysis of gene expression profiles at the single-cell level\r 2. Utilizes microfluidic techniques for high-throughput single-cell RNA sequencing\r 3. Allows for the identification of cell types and characterization of cell populations within heterogeneous samples\r 4. Provides a platform for studying gene expression dynamics in individual cells\r 5. Facilitates the discovery of rare cell types and transitional cell states |
Bioinformatics | Genetics | Biological Sciences | Single-Cell RNA Sequencing, Gene Expression Analysis, Microfluidics, Cellular Heterogeneity, Transcriptomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/drop-seq | Anvil: 2.5.2 | Computational Tool | ||||
dropest | Anvil | Dropest is a pipeline for initial analysis of droplet-based single-cell RNA-seq data. | dropest is a statistical software package for carrying out robust power and sample size calculations in two-sample comparisons. | Some core features of dropest include robust power calculations, sample size calculations, adjustment for non-normality in data, and computation of power curves. | Tool | Statistical Software, Power Calculations, Sample Size Calculations | Statistics & Probability | Anvil: https://www.rcac.purdue.edu/software/dropest | Anvil: 0.8.6 | Statistical Software | ||||||
dsmml | Delta | dsmml is a deep learning library specifically designed for molecular machine learning applications. It offers a range of tools and techniques tailored for computational chemistry and drug discovery tasks. | The core features of dsmml include support for deep learning models such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for molecular structure analysis, molecular property prediction, ligand-protein interaction analysis, and virtual screening. It also provides pre-trained models, dataset management tools, and visualization capabilities for interpreting model results. | Deep Learning Library | Physical Chemistry | Chemical Sciences | Deep Learning, Molecular Machine Learning, Computational Chemistry, Drug Discovery | Other Chemical Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Molecular Machine Learning Library | ||||||
dsuite | Anvil | Dsuite provides a fast calculation of Patterson's D (ABBA-BABA) and the f4-ratio statistics across many populations/species. Description Source: https://github.com/millanek/Dsuite |
Dsuite is a Python package for processing, analyzing, and visualizing longitudinal and survival data in a user-friendly way. It is designed to facilitate data exploration, estimation of parametric and non-parametric models, and visualization of results for longitudinal and survival data analysis. | Some of the core features of dsuite include data preprocessing, model estimation for longitudinal and survival analysis, visualization tools for exploring and interpreting results, and integration with other Python libraries for statistical analysis and data visualization. | https://github.com/millanek/Dsuite?tab=readme-ov-file#commands-v05-r53 | Python Library | Longitudinal Data Analysis, Survival Analysis | Biostatistics | Python Library, Data Analysis, Data Visualization | https://github.com/millanek/Dsuite | Statistics & Probability | https://github.com/millanek/tutorials/tree/master/analysis_of_introgression_with_snp_data | Anvil: https://www.rcac.purdue.edu/software/dsuite | Anvil: 0.4.R43, 0.5.R44 | Data Analysis Tool | |
dualsphysics | Faster | DualSPHysics is a popular open-source computational fluid dynamics software package based on the Smoothed Particle Hydrodynamics (SPH) method. It allows for the simulation of free-surface flows, fluid-structure interactions, and complex fluid dynamics phenomena. | Smoothed Particle Hydrodynamics (Sph) Simulations, Simulation Of Free-Surface Flows, Fluid-Structure Interactions Modeling, Parallel Computing Capabilities, Open-Source & Customizable, User-Friendly Interface | Computational | Computational Fluid Dynamics | Fluid Dynamics | Computational Fluid Dynamics, Fluid Dynamics, Open-Source Software, Parallel Computing, Sph Method | Physical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 5.0.175-Cuda-11.4.1 | Simulation Software | |||||
dyninst | Delta | Dyninst is a versatile and powerful binary instrumentation and analysis tool that provides capabilities for runtime code analysis, modification, and monitoring in C, C++, and Fortran applications. | 1. Binary instrumentation for code analysis and modification.\r 2. Dynamic analysis of program behavior.\r 3. Program monitoring during runtime.\r 4. Support for C, C++, and Fortran applications.\r 5. Versatile and flexible for various use cases. |
Tool | Binary Instrumentation, Code Analysis, Runtime Monitoring | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Instrumentation & Analysis | ||||||||
easybuild | Aces, Faster, Kyric | EasyBuild is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way. Description Source: https://docs.easybuild.io/what-is-easybuild/ |
EasyBuild is an open-source framework for building and installing software packages on High-Performance Computing (HPC) systems. It aims to make building software easier for system administrators and users on HPC systems by automating the build process. | Automates The Building & Installation Of Software Packages, Supports A Wide Range Of Software Packages & Libraries, Provides Easy-To-Use Configuration Options, Designed For Hpc Systems | https://easybuild.readthedocs.io/en/latest/ | Build Automation | Software Building, High-Performance Computing, Automation | https://easybuild.io/ | Engineering & Technology | https://tutorial.easybuild.io/ https://docs.easybuild.io/using-easybuild/#specifying_easyconfigs https://docs.easybuild.io/typical-workflow-example/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.7.1, 4.8.0, 4.8.2, 4.9.0 Faster: 4.5.1, 4.5.4, 4.5.5, 4.6.0, 4.6.2, 4.7.0, 4.7.1, 4.7.2, 4.8.2 Kyric: 4.3.0 |
Developer Tools | |||
easybuild-aces | Aces | EasyBuild environment variables for building system software in /tmp and installing in /sw/eb on aces.hprc.tamu.edu Description Source: https://hprc.tamu.edu/software/aces/# |
EasyBuild-ACES is a collection of EasyBuild framework recipes for building commonly used software packages within the Army Combat Capabilities Development Command Army Research Laboratory (CCDC-ARL) Computational and Information Sciences Directorate (CISD) Advanced Computing, Engineering and Software (ACES) research group. | EasyBuild-ACES provides recipes for building software packages often used by the CCDC-ARL CISD ACES research group, allowing for easy deployment and management of these tools. | https://easybuild.readthedocs.io/en/latest/ | Tools | Software Engineering, Systems, & Development | Computer & Information Sciences | Software Development, Tools, Packages | https://easybuild.io/ | Computer & Information Sciences | https://tutorial.easybuild.io/ https://docs.easybuild.io/using-easybuild/#specifying_easyconfigs https://docs.easybuild.io/typical-workflow-example/ |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0 | Software Engineering & Development | |
easybuild-aces-myeb | Aces | User EasyBuild environment for aces.hprc.tamu.edu in $SCRATCH/eb. Description Source: https://hprc.tamu.edu/software/aces/# |
https://easybuild.readthedocs.io/en/latest/ | https://easybuild.io/ | https://tutorial.easybuild.io/ https://docs.easybuild.io/using-easybuild/#specifying_easyconfigs https://docs.easybuild.io/typical-workflow-example/ |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0 | Software Repo | ||||||||
easybuild-aces-scratch | Aces | User EasyBuild environment for aces.hprc.tamu.edu in $SCRATCH/eb. Description Source: https://hprc.tamu.edu/software/aces/# |
https://easybuild.readthedocs.io/en/latest/ | https://easybuild.io/ | https://tutorial.easybuild.io/ https://docs.easybuild.io/using-easybuild/#specifying_easyconfigs https://docs.easybuild.io/typical-workflow-example/ |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0 | Software Repo | ||||||||
easybuild-aces-tmp | Aces | EasyBuild environment variables for building in /tmp and installing in /sw/eb on aces.hprc.tamu.edu. Description Source: https://hprc.tamu.edu/software/aces/# |
EasyBuild is a software build and installation framework for high-performance computing (HPC) systems. The aces-tmp tool is a temporary directory management tool that is part of the EasyBuild framework. | 1. Manages temporary directories for the EasyBuild software build and installation framework.\r 2. Helps in organizing and cleaning up temporary build directories for optimized performance.\r 3. Streamlines the build process by efficiently managing temporary storage. |
https://easybuild.readthedocs.io/en/latest/ | Tool | Science & Engineering Education | Infrastructure & Instrumentation | Software Build, Installation Framework, Hpc Systems, Temporary Directory Management | https://easybuild.io/ | Engineering & Technology | https://tutorial.easybuild.io/ https://docs.easybuild.io/using-easybuild/#specifying_easyconfigs https://docs.easybuild.io/typical-workflow-example/ |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0 | Utilities | |
easybuild-faster | Faster | EasyBuild-Faster is an extension of EasyBuild, a software build and installation framework for high-performance computing (HPC) systems. EasyBuild-Faster focuses on optimizing the software build process to reduce build times and improve overall efficiency on HPC systems. | Optimizes Software Build Process For Hpc Systems, Reduces Build Times, Improves Overall Efficiency, Works As An Extension Of Easybuild | Software Framework | Hpc, Software Build Optimization, High-Performance Computing | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0 | Development & Optimization Tools | |||||||
easybuild-faster-myeb | Faster | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0 | |||||||||||||
easybuild-faster-scratch | Faster | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0 | |||||||||||||
easybuild-faster-tmp | Faster | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0 | |||||||||||||
easysfs | Anvil | easySFS is a tool for the effective selection of population size projection for construction of the site frequency spectrum. edta: ed | easysfs is a software tool designed for population genomics analysis, specifically focusing on Site Frequency Spectrum (SFS) data. | The software allows users to estimate basic population genetic parameters such as theta and Tajima's D, perform neutrality tests, and visualize and analyze the SFS data. | Tool | Population Genomics | Genomics | Population Genomics, Genetic Analysis, Sfs Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/easysfs | Anvil: 1.0 | Genomic Analysis | ||||
ecbuild | Aces, Faster | ECbuild is a CMake-based build system, consisting of a collection of CMake macros and functions that ease the managing of software build systems. Description Source: https://github.com/ecmwf/ecbuild |
ecBuild is a CMake-based build system generator for Earth system model (ESM) projects. It focuses on enabling easy configuration and management of complex ESM projects by automating the generation of build systems. | Automated Generation Of Cmake-Based Build Systems, Configuration Management For Earth System Model Projects, Integration With Esm Workflows & Components, Facilitates Model Coupling & Parallel Execution | https://ecbuild.readthedocs.io/en/latest/ | Build System Generator | Build System Generator, Earth System Model, Cmake-Based, Esm Project, Model Coupling, Parallel Execution | https://github.com/ecmwf/ecbuild | Earth & Environmental Sciences | https://github.com/ecmwf/ecbuild/tree/develop/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.7.0, 3.8.0 Faster: 3.7.0, 3.8.0 |
Development Tools | |||
eccodes | Aces, Faster | ecCodes is a package developed by ECMWF which provides an application programming interface and a set of tools for decoding and encoding messages in different WMO formats. Description Source: https://github.com/ecmwf/eccodes |
eccodes is a software package for encoding/decoding and manipualting meteorological data in GRIB format. It provides a large number of functionalities to work with data in meteorology, oceanography, and climatology. | 1. Encode and decode GRIB data\r 2. Manipulate meteorological data\r 3. Support for various meteorological data formats\r 4. Extensive functionalities for data processing and analysis |
https://confluence.ecmwf.int/display/ECC/Documentation | Data Encoding/Decoding | Meteorology | Atmospheric Sciences | Grib Data, Meteorology, Oceanography, Climatology | https://confluence.ecmwf.int/display/ECC/ecCodes+Home | Earth & Environmental Sciences | https://confluence.ecmwf.int/display/ECC/API+examples https://confluence.ecmwf.int/display/ECC/Training+material |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.24.2, 2.27.0, 2.31.0 Faster: 2.22.1, 2.24.2 |
Data Processing | |
edlib | Faster | Edlib is an open-source library for sequence alignment using edit (Levenshtein) distance and pairwise alignment. It includes several alignment algorithms and methods for comparing sequences. | 1. Supports various alignment algorithms such as Edit distance, Hamming distance, and NW (Needleman-Wunsch) global alignment.\r 2. Provides functions for pairwise alignment of sequences and computing their similarity.\r 3. Includes methods for approximate string matching and searching.\r 4. Allows users to set custom parameters for alignment and scoring.\r 5. Written in C language with bindings available for Python and other programming languages. |
Bioinformatics | Sequence Alignment, Edit Distance, Pairwise Alignment | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.3.8.Post1-Python-3.7.4 | Library | |||||||
edta | Anvil | Edta is developed for automated whole-genome de-novo TE annotation and benchmarking the annotation performance of TE libraries. eggnog-mapper: eggnog- | EDTA (Enhanced De Novo Transcriptome Assembler) is a software tool designed for transcriptome assembly from RNA-Seq data. It aims to accurately reconstruct full-length transcripts and improve gene annotation. | 1. De novo transcriptome assembly from RNA-Seq data\r 2. Reconstruction of full-length transcripts\r 3. Improvement of gene annotation\r 4. Identification of alternatively spliced isoforms\r 5. Estimation of expression levels |
Tool | Genetics | Biological Sciences | Transcriptome Assembly, RNA-Seq, Gene Annotation | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/edta | Anvil: 1.9.6, 2.0.0 | Bioinformatics | ||||
eggnog-mapper | Anvil | Eggnog-mapper is a tool for fast functional annotation of novel sequences. | EggNOG-mapper is a tool that allows functional annotation of non-model species using orthology-based methods. It leverages precomputed clusters of orthologous genes from multiple species to predict gene function through orthology transfer. | Functional Annotation Of Non-Model Species, Orthology-Based Methods, Gene Function Prediction Through Orthology Transfer | Bioinformatics Tool | Genomics | Bioinformatics | Functional Annotation, Orthology, Gene Function Prediction | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/eggnog-mapper | Anvil: 2.1.7 | Annotation Tool | ||||
eigen | Aces, Anvil, Darwin, Expanse, Faster, Stampede3 | Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. Description Source: https://eigen.tuxfamily.org/index.php?title=Main_Page |
Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. | 1. Straightforward API for matrix operations\r 2. Support for dense and sparse matrices\r 3. Various linear algebra and numerical solvers\r 4. Eigenvalues and eigenvectors computations\r 5. Fast and efficient computation |
https://eigen.tuxfamily.org/dox/ | Linear Algebra Library | Linear Algebra, Numerical Computation, C++ Library | https://eigen.tuxfamily.org/ | Computer & Information Sciences | https://eigen.tuxfamily.org/dox/GettingStarted.html | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/eigen Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 3.3.8, 3.3.9, 3.4.0 Anvil: 3.3.9 Expanse: Aoih524, Rarzo6S, ... Faster: 3.3.7, 3.3.8, 3.3.9, 3.4.0 Stampede-3: 3.4.0 |
Library | |||
einops | Aces, Faster | Einops is a python library which allows for Flexible and powerful tensor operations for readable and reliable code. Supports numpy, pytorch, tensorflow, jax, and others. Description Source: https://github.com/arogozhnikov/einops |
einops is a Python library for tensor operations and reshaping with a focus on readability and flexibility. It provides a more intuitive and concise way of manipulating tensor dimensions in deep learning frameworks. | 1. Simple and expressive syntax for tensor reshaping operations. 2. Supports various tensor operations like permutation, transpose, reduction, etc. 3. Integration with popular deep learning frameworks like PyTorch and TensorFlow. 4. Efficient and easy-to-understand code for tensor manipulations. | https://einops.rocks/#api | Python Library | Artificial Intelligence & Intelligent Systems | Computer Science | Python Library, Tensor Manipulation, Deep Learning Frameworks | https://einops.rocks/ | Computer & Information Sciences | https://einops.rocks/1-einops-basics/ | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.4.1 Faster: 0.3.2, 0.4.1, 0.6.0 |
Library | |
elfutils | Aces, Faster | elfutils is a collection of utilities and libraries to read, create and modify ELF binary files, find and handle DWARF debug data, symbols, thread state and stacktraces for processes and core files on GNU/Linux. Description Source: https://sourceware.org/elfutils/ |
elfutils is a collection of various binary tools for working with ELF files. It includes utilities for analyzing, manipulating, and creating programs and object files in the Executable and Linkable Format (ELF). These tools are commonly used by programmers, debuggers, and system administrators to inspect and modify ELF binaries. | 1. Reading and analyzing ELF files\r 2. Modifying and updating ELF binaries\r 3. Debugging programs and libraries\r 4. Extracting and examining symbol tables and section headers\r 5. Inspecting and manipulating core dump files\r 6. Disassembling machine code\r 7. Handling DWARF debugging information\r 8. Checking and correcting ELF header information |
https://github.com/roolebo/elfutils/blob/master/libelf/libelf.h | Binary Tool, Elf Files, Debugging, Programming | https://sourceware.org/elfutils/ | https://access.redhat.com/documentation/en-us/red_hat_developer_toolset/7/html/user_guide/chap-elfutils | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.187, 0.189 Faster: 0.182, 0.185, 0.187, 0.189 |
Utilities | |||||
elpa | Aces, Expanse, Faster, Ookami | The publicly available ELPA library provides highly efficient and highly scalable direct eigensolvers for symmetric (hermitian) matrices. Descripiton Source:https://elpa.mpcdf.mpg.de/ABOUT_ELPA.html | ELPA (Eigenvalue SoLvers for Petaflop Applications) is a library for solving the standard and generalized eigenvalue problems for dense Hermitian matrices. It is designed for high-performance computing systems and utilizes highly scalable algorithms to achieve high efficiency. | Solves Standard & Generalized Eigenvalue Problems For Dense Hermitian Matrices, Optimized For High-Performance Computing Systems, Utilizes Highly Scalable Algorithms For Efficiency, Suitable For Parallel Computing | https://elpa.mpcdf.mpg.de/documentation/doxygen/ELPA_DOXYGEN_PAGES/ELPA-2024.03.001.rc1/html/index.html | Library | Linear Algebra, Eigenvalue Problems, High-Performance Computing, Scalable Algorithms | https://elpa.mpcdf.mpg.de/ | Computer & Information Sciences | https://gitlab.mpcdf.mpg.de/elpa/elpa/-/blob/master/documentation/USERS_GUIDE.md | Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 2021.11.001, 2022.05.001-Cuda-11.8.0, 2022.05.001, 2023.05.001 Expanse: Eq4324U, Fyc633Z Faster: 2021.05.001, 2021.11.001, 2022.05.001Cuda-11.8.0 Ookami: 2016.11.001.Pre |
Numerical Library | |||
emacs | Aces, Anvil, Darwin | GNU Emacs is an extensible, customizable, free/libre text editor. Description Source: https://www.gnu.org/savannah-checkouts/gnu/emacs/emacs.html |
Emacs is a highly customizable, extensible, and self-documenting text editor. It is known for its powerful editing capabilities, which include content-aware editing, syntax highlighting, and a wide range of plugins and extensions. | Emacs offers a range of features like syntax highlighting, auto-indentation, content-aware editing, integrated version control, and a large collection of plugins and packages (e.g., Org mode for organizing notes and tasks). It supports various programming languages and can be customized using Emacs Lisp. | https://www.gnu.org/software/emacs/manual/html_node/emacs/index.html | Text Editor | Text Editor, Customizable, Extensible, Self-Documenting | https://www.gnu.org/software/emacs/ | Computer & Information Sciences | https://www.gnu.org/software/emacs/manual/html_node/emacs/Basic.html | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/emacs |
Aces: 27.2, 28.2 Anvil: 27.2 |
Productivity Tool | |||
emboss | Anvil, Expanse, Faster | Emboss is 'The European Molecular Biology Open Software Suite' | EMBOSS is a comprehensive software analysis package for biological sequence data. It provides over 200 tools for sequence alignment, database searching, pattern matching, motif identification, and more. EMBOSS is widely used in bioinformatics and computational biology research. | Sequence Alignment, Database Searching, Motif Identification, Pattern Matching, Phylogenetic Analysis | Analysis Tool | Sequence Analysis | Bioinformatics | Bioinformatics, Computational Biology, Sequence Analysis, Biological Data | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/emboss Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 6.6.0 Expanse: 6.6.0 Faster: 6.6.0-Java-13, 6.6.0 |
Sequence Analysis Tools | ||||
enchant-2 | Aces, Faster | Enchant aims to provide a simple but comprehensive abstraction for dealing with different spell checking libraries in a consistent way. A client, such as a text editor or word processor, need not know anything about a specific spell-checker, and since all back-ends are plugins, new spell-checkers can be added without needing any change to the program using Enchant. | Enchant is a spellchecking library that provides a consistent API for invoking spellchecking routines across different platforms. Enchant-2 is the newer version of the Enchant spellchecking framework. | 1. Cross-platform spellchecking capabilities. 2. Consistent API for invoking spellchecking routines. 3. Supports multiple backends for spellchecking. 4. Customizable dictionaries and language support. | Spellchecking | Spellchecking, Library, Cross-Platform, Spellchecking Routines | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.3.3 Faster: 2.3.3 |
Spellchecking Library | ||||||
energyplus | Faster | EnergyPlus is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water use in buildings. It allows users to evaluate the combined performance of building energy and environmental control systems. | Detailed Building Energy & Environmental Simulation, Support For Various Hvac Systems & Control Strategies, Advanced Fenestration Modeling Capabilities, Weather Data Integration For Accurate Simulations, Parametric Analysis & Optimization Features | Simulation Software | Building Energy Efficiency | Environmental Engineering | Energy Simulation, Building Performance, Environmental Control, Parametric Analysis, Building Energy Consumption | Engineering & Technology | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 9.3.0, 23.1.0 | Building Performance Simulation | |||||
ensembl-vep | Anvil | VEP determines the effect of your variants (SNPs, insertions, deletions, CNVs or structural variants) on genes, transcripts, and protein sequence, as well as regulatory regions. Description Source: https://useast.ensembl.org/info/docs/tools/vep/index.html |
https://useast.ensembl.org/info/docs/tools/vep/script/index.html#contents | Sciences | Biology | https://useast.ensembl.org/info/docs/tools/vep/index.html | https://useast.ensembl.org/info/docs/tools/vep/script/vep_tutorial.html https://useast.ensembl.org/info/docs/tools/vep/script/vep_example.html |
Anvil: https://www.rcac.purdue.edu/software/ensembl-vep | Anvil: 106.1, 107.0, 108.2 | Bioinformatics | ||||||
entrezdirect | Expanse | Entrez Direct (EDirect) provides access to the NCBI's suite of interconnected databases (publication, sequence, structure, gene, variation, expression, etc.) from a UNIX terminal window. | https://www.ncbi.nlm.nih.gov/books/NBK179288/ | https://github.com/Klortho/edirect | https://www.ncbi.nlm.nih.gov/books/NBK565821/ https://hpc.nih.gov/apps/edirect.html |
Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: U7Oel2N, ... | |||||||||
epic2 | Anvil | epic2 is an ultraperformant Chip-Seq broad domain finder based on SICER. | epic2 is a software tool for identifying genomic regions enriched with ChIP-seq signal. It is specifically designed for identifying enriched regions in large datasets, offering high sensitivity and specificity in peak calling. | 1. Efficient identification of enriched genomic regions in large ChIP-seq datasets.\r 2. High sensitivity and specificity in peak calling.\r 3. User-friendly interface for ease of use.\r 4. Capable of handling large-scale data analysis. |
Data Analysis Tool | Genomics | Bioinformatics | Chip-Seq, Peak Calling, Genomic Regions | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/epic2 | Anvil: 0.0.51, 0.0.52 | Bioinformatics Tool | ||||
esm | Faster | ESM (Earth System Modeling) is a software tool designed for simulating and studying complex interactions within the Earth system, including the atmosphere, oceans, land surface, and cryosphere. It enables researchers to investigate climate variability, climate change, and environmental processes. | Earth System Modeling, Climate Variability & Change Simulation, Environmental Process Analysis, Atmosphere-Ocean-Land Interactions | Simulation Tool | Earth System Modeling, Climate Simulation, Environmental Processes, Earth System Interactions | Earth & Environmental Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.0.0 | Modeling Software | |||||||
esmf | Aces, Expanse, Faster | The Earth System Modeling Framework (ESMF) is a suite of software tools for developing high-performance, multi-component Earth science modeling applications. Such applications may include a few or dozens of components representing atmospheric, oceanic, terrestrial, or other physical domains, and their constituent processes (dynamical, chemical, biological, etc.). Description Source: https://earthsystemmodeling.org/docs/release/latest/ESMF_usrdoc/node2.html |
The Earth System Modeling Framework (ESMF) is a software infrastructure for building and coupling weather, climate, and related Earth science models. It provides a flexible and reusable software architecture that facilitates the use, development, and coupling of Earth science models. | Supports Modeling Weather, Climate, & Earth Science Phenomena, Provides Infrastructure For Building & Coupling Models, Facilitates Interoperability & Data Exchange Between Models, Offers Tools For Parallel Computing & Performance Optimization | https://earthsystemmodeling.org/doc/ | Computational Software | Atmospheric Sciences | Earth & Environmental Sciences | Earth System Modeling, Climate Modeling, Weather Modeling, Model Coupling, Earth Science | https://earthsystemmodeling.org/ | Physical Sciences | https://earthsystemmodeling.org/tutorials/ | Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 8.0.1, 8.1.1, 8.3.0 Expanse: Nvkj3Wb Faster: 8.1.1, 8.2.0, 8.3.0 |
Modeling Framework | |
evidencemodeler | Anvil | Evidencemodeler is a software combines ab intio gene predictions and protein and transcript alignments into weighted consensus gene structures. exonerat | EvidenceModeler (EM) is a flexible and customizable pipeline for generating gene structure annotations by integrating evidence from various prediction programs and transcriptomic data. | Combines Evidence From Multiple Sources To Generate Accurate Gene Structures, Supports Integration Of Predicted Gene Models, Transcriptome Alignments, Protein Homology Evidence, & More, Allows Customization Of Evidence Weightings & Parameters For Gene Structure Prediction, Ability To Incorporate User-Defined Gene Models & Evidence Sources | Pipeline | Genomics | Bioinformatics | Gene Prediction, Annotation, Bioinformatics, Transcriptomics, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/evidencemodeler | Anvil: 1.1.1 | Gene Prediction Tool | ||||
exabayes | Expanse | ExaBayes is a software package for Bayesian tree inference. It is particularly suitable for large-scale analyses on computer clusters. | ExaBayes is a software package for Bayesian inference on large phylogenetic trees using parallel computing techniques. | ExaBayes offers efficient and scalable Markov chain Monte Carlo (MCMC) algorithms for analyzing very large Bayesian phylogenetic datasets. It is specifically designed to handle massive datasets on high-performance computing (HPC) systems. The software supports various models of sequence evolution and tree priors, enabling complex phylogenetic analyses. ExaBayes leverages GPU acceleration for rapid computation and supports MPI for parallel processing. | Phylogenetic Software | Evolutionary Biology | Ecology | Bayesian Inference, Phylogenetics, Parallel Computing, Mcmc, Hpc | Biological Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 1.5.1 | Bioinformatics | ||||
exiv2 | Aces, Faster | Exiv2 is a Cross-platform C++ library and a command line utility to manage image metadata. | Exiv2 is a C++ library and a command-line utility to manage image metadata. It provides fast and easy read and write access to the Exif, IPTC, and XMP metadata of images in various formats. | 1. Supports reading and writing Exif metadata in various image formats\r 2. Supports reading and writing IPTC and XMP metadata\r 3. Command-line utility for batch processing of image metadata\r 4. Embeds, extracts, and deletes metadata from images\r 5. Supports various image formats including JPEG, TIFF, PNG, and more |
Metadata Management | Metadata Management, Image Processing, Command-Line Utility | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.27.5 Faster: 0.27.5 |
Library, Utility | ||||||
exonerate | Anvil | Exonerate is a generic tool for pairwise sequence comparison/alignment. | Exonerate is a versatile tool for sequence alignment and homology search. It is widely used for comparison of protein and nucleotide sequences against a wide range of genomic databases. | Flexible Sequence Alignment & Homology Search Algorithms, Support For Protein-Protein, DNA-DNA, Protein-DNA, & Est-Genome Alignments, Ability To Handle Large Genomic Datasets Efficiently, Customizable Scoring Parameters For Alignment, Output In Various Formats For Downstream Analysis | Bioinformatics Tool | Genomics | Bioinformatics | Sequence Alignment, Homology Search, Bioinformatics, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/exonerate | Anvil: 2.4.0 Faster: 2.4.0 |
Sequence Alignment | ||||
expansionhunter | Anvil | Expansion Hunter: a tool for estimating repeat sizes. | ExpansionHunter is a set of tools for detecting repeat expansions in whole genome sequencing data. It is specifically designed to identify repeat length differences that are associated with genetic diseases. ExpansionHunter scans the genome for such expansions and provides detailed information and visualizations to assist in variant interpretation. | Detection Of Repeat Expansions In Human Genomes, Identification Of Repeat Length Differences Linked To Genetic Diseases, Visualization Tools For Variant Interpretation, Analysis Of Whole Genome Sequencing Data | Data Analysis Tool | Medical Biotechnology | Genetics | Genetic Diseases, Repeat Expansions, Variant Interpretation, Whole Genome Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/expansionhunter | Anvil: 4.0.2 | Bioinformatics | ||||
expat | Aces, Faster, Kyric | Expat is a stream-oriented XML parser library written in C and excels with files too large to fit RAM, and where performance and flexibility are crucial. Description Source: https://libexpat.github.io/ |
Expat is an XML parser library written in C. It is a fast and lightweight library that is designed for high-performance applications. | 1. Supports parsing of XML documents\r 2. Provides API for developers to implement XML parsing in their applications\r 3. Fast and efficient parsing of XML\r 4. Easy to integrate with various programming languages |
https://libexpat.github.io/doc/api/latest/ | Xml Parser | Xml Parser, Library | https://libexpat.github.io/ | Computer & Information Sciences | https://libexpat.github.io/doc/getting-started/ https://www.xml.com/pub/1999/09/expat/index.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.2.9, 2.4.1, 2.4.8, 2.4.9, 2.5.0 Faster: 2.2.5, 2.2.7, 2.2.9, 2.4.1, 2.4.8, 2.4.9, 2.5.0 |
Library | |||
expecttest | Aces, Faster | This library implements expect tests (also known as "golden" tests). Expect tests are a method of writing tests where instead of hard-coding the expected output of a test, you run the test to get the output, and the test framework automatically populates the expected output. Description Source: https://github.com/ezyang/expecttest |
expecttest is a versatile testing tool for software developers that allows for the automation of interactive applications, system administration tasks, and more. It provides a simple scripting language for driving applications and processes under test, making it easy to automate testing workflows. | Automating Interactive Applications, Scripting Language For Testing, Automation Of System Administration Tasks | https://github.com/ezyang/expecttest/blob/main/README.md | Automation Tool | Testing Tool, Automation, Scripting, Software Development | https://github.com/ezyang/expecttest | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.1.3, 0.1.5 Faster: 0.1.3, 0.1.5 |
Testing Tool | |||||
extrae | Kyric | Extrae is a performance analysis tool designed to capture and analyze trace data from parallel and distributed applications. It allows users to monitor and examine the behavior of their applications in terms of performance, identifying potential bottlenecks and areas for optimization. | Capture & Analyze Trace Data From Parallel Applications, Identify Performance Bottlenecks, Optimize Application Performance, Monitor Application Behavior | https://tools.bsc.es/doc/html/extrae/api.html | Tool | Performance Analysis, Trace Data, Parallel Applications, Distributed Applications | https://tools.bsc.es/extrae | Computer & Information Sciences, Software Engineering, Systems, & Development, Engineering & Technology, Training, Infrastructure & Instrumentation | https://tools.bsc.es/doc/html/extrae/quick-guide.html https://tools.bsc.es/doc/html/extrae/examples.html |
Kyric: 3.7.0 | Performance Analysis | |||||
eztrace | Aces | EZTrace is a tool that aims at generating automatically execution trace from HPC programs. | eztrace is a tool that provides a set of library calls that can be used to trace the evolution of applications during their execution. It helps in performance analysis by collecting information about function calls, communication patterns, and execution characteristics. | 1. Tracing function calls and communication patterns\r 2. Performance analysis\r 3. Execution characteristics monitoring\r 4. Profiling applications |
Library Tool | Performance Analysis, Function Call Tracing, Profiling, Monitoring | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 2.1 | Performance Analysis Tool | ||||||
fasta3 | Anvil | Fasta3 is a suite of programs for searching nucleotide or protein databases with a query sequence. | fasta3 is a suite of tools for searching nucleotide or protein databases with a query sequence, as well as for conducting multiple sequence alignment. | fasta3 includes tools for database searching, sequence alignment, and motif finding. It provides efficient methods for comparing DNA or protein sequences. | Sequence Analysis Tool | Bioinformatics, Sequence Analysis, Alignment | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fasta3 | Anvil: 36.3.8 | Bioinformatics Tool | ||||||
fastai | Aces | fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. Description Source: https://docs.fast.ai/#about-fastai |
The fastai library simplifies training fast and accurate neural networks using modern best practices. It is built on top of PyTorch and provides many high-level abstractions to make it easy to train state-of-the-art models with little code. | 1. High-level API for training deep learning models. 2. Implements cutting-edge techniques in an accessible way. 3. Provides pre-trained models for transfer learning. 4. Includes tools for interpretability and visualization. | https://docs.fast.ai/ | Machine Learning Framework | Machine Learning, Deep Learning | Artificial Intelligence & Intelligent Systems | Deep Learning, Neural Networks, Machine Learning, Pytorch | https://www.fast.ai/ | Computer & Information Sciences | https://course.fast.ai/ https://course.fast.ai/Lessons/part2.html https://course18.fast.ai/lessonsml1/lesson1.html https://www.youtube.com/playlist?list=PLfYUBJiXbdtSLBPJ1GMx-sQWf6iNhb8mM |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 2.7.10 | Libraries | |
fastani | Anvil, Bridges-2 | FastANI is developed for fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI). ANI is defined as mean nucleotide identity of orthologous gene pairs shared between two microbial genomes. FastANI supports pairwise comparison of both complete and draft genome assemblies. Description Source: https://github.com/ParBLiSS/FastANI |
fastANI is a tool for computing average nucleotide identity (ANI) and relatedness between bacterial and archaeal genomes at high speed. It uses MinHash to estimate ANI values in a fraction of the time compared to traditional methods. | 1. Calculation of average nucleotide identity (ANI) between microbial genomes. 2. Utilizes MinHash algorithm for fast ANI estimation. 3. Supports large-scale genome comparisons efficiently. 4. Provides a rapid alternative to traditional ANI calculation methods. | https://github.com/ParBLiSS/FastANI/blob/master/README.md | Genome Analysis Tool | Genomics | Biology | Bioinformatics, Genome Comparison, Bacterial Genomes | https://github.com/ParBLiSS/FastANI | Biological Sciences | https://hackmd.io/@AstrobioMike/Nadjet-fastANI-example | Anvil: https://www.rcac.purdue.edu/software/fastani Bridges-2: https://www.psc.edu/resources/software/fastani |
Anvil: 1.32, 1.33 Bridges-2: 1.33 |
Bioinformatics Tool | |
fastcore | Faster | fastcore is a utility library that provides a set of core functions and classes to improve the productivity and readability of Python code. It includes various utilities for data manipulation, functional programming, and general-purpose task optimization. | Provides Core Functions & Classes For Python Programming, Includes Utilities For Data Manipulation & Functional Programming, Optimizes General-Purpose Tasks For Improved Productivity | Python Library | Python Library, Utility Library, Data Manipulation, Functional Programming | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.3.27 | Library | |||||||
fastp | Anvil, Expanse | Fastp is an ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging, etc). | fastp is a tool designed for pre-processing high throughput sequencing data faster and more efficiently. | The core features of fastp include adapter trimming, quality filtering, quality control, and error correction of sequencing data. | Tool | Genomics | Bioinformatics | Bioinformatics, Sequencing, Data Processing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fastp Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 0.20.1, 0.23.2 Expanse: Vihdvcu |
Data Processing | ||||
fastq_pair | Anvil | Fastq_pair is used to match up paired end fastq files quickly and efficiently. | fastq_pair is a tool for pairing and sorting paired-end reads in FASTQ format. It is designed to efficiently process large volumes of paired-end sequencing data by identifying matching read pairs and organizing them for downstream analysis. | Pairing & Sorting Paired-End Reads In Fastq Format, Efficient Processing Of Large Volumes Of Sequencing Data, Identification Of Matching Read Pairs, Organization Of Paired-End Reads For Downstream Analysis | Data Processing Tool | Bioinformatics, Computational Biology, Sequencing Data, Paired-End Reads, Fastq Format | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fastq_pair | Anvil: 1.0 | Bioinformatics Tool | ||||||
fastq-scan | Anvil | Fastq-scan reads a FASTQ from STDIN and outputs summary statistics (read lengths, per-read qualities, per-base qualities) in JSON format. | fastq-scan is a tool for batch scanning and processing FASTQ files to extract quality control metrics for Next-Generation Sequencing (NGS) data. | Batch Scanning Of Fastq Files, Quality Control Metrics Extraction For Ngs Data, Efficient Processing Of Large Datasets | Bioinformatics | Genomics | Genetics | Ngs Data Analysis, Quality Control, Fastq File Processing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fastq-scan | Anvil: 1.0.0 | Ngs Quality Control | ||||
fastq-tools | Bridges-2 | Small utilities for working with fastq sequence files. | fastq-tools is a collection of simple and efficient command-line tools for processing FASTQ files commonly used in bioinformatics. It provides various utilities for quality control, filtering, and manipulation of raw sequencing data in FASTQ format. | Some of the core features of fastq-tools include quality assessment, adapter trimming, filtering by quality scores, file format conversion, and extraction of specific sequences from FASTQ files. It aims to streamline common preprocessing tasks in next-generation sequencing data analysis pipelines. | Data Processing Tool | Genomics | Bioinformatics | Bioinformatics, Ngs, Genome Sequencing, Sequence Analysis | Biological Sciences | Bridges-2: https://www.psc.edu/resources/software/fastq-tools | Bridges-2: 0.8 | Command-Line Tools | ||||
fastqc | Aces, Anvil, Bridges-2, Expanse, Faster | FastQC aims to provide a QC report which can spot problems which originate either in the sequencer or in the starting library material. Whereas Most sequencers will generate a QC report as part of their analysis pipeline, but this is usually only focused on identifying problems which were generated by the sequencer itself. Description Source: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/1%20Introduction/1.1%20What%20is%20FastQC.html |
FastQC is a quality control tool for high throughput sequence data. It provides a detailed overview of the quality and potential issues in sequencing data generated by high throughput sequencing pipelines. | Generate Quality Control Reports For Sequencing Data, Identify Potential Sequencing Errors & Biases, Visualize Sequence Quality Scores, Per Base Sequence Content, Gc Content, Sequence Duplication Levels, & More, Supports Various Sequencing Platforms & Data Formats | https://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/ | Analysis Tool | Sciences | Biology | Quality Control, High Throughput Sequencing, Sequence Analysis, Bioinformatics | https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ | Biological Sciences | https://www.youtube.com/watch?v=bz93ReOv87Y | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/fastqc Bridges-2: https://www.psc.edu/resources/software/fastqc Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.11.9-Java-11 Anvil: 0.11.9, 0.12.1 Bridges-2: 0.11.9 Expanse: 0.11.7 Faster: 0.11.9-Java-11 |
Quality Control Tool | |
fastspar | Anvil | Fastspar is a tool for rapid and scalable correlation estimation for compositional data. | fastspar is a Python package that implements a fast version of SparCC, a correlation method tailored for compositional data commonly found in microbiome studies. | fastspar provides a quicker alternative to SparCC, especially for large datasets, by utilizing an improved algorithm for computing compositional correlation values. It is designed to handle high-dimensional and sparse data typically encountered in microbiome research. | Computational Software | Microbiome, Correlation, Compositional Data | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fastspar | Anvil: 1.0.0 | Python Library | ||||||
faststructure | Anvil | fastStructure is an algorithm for inferring population structure from large SNP genotype data. It is based on a variational Bayesian framework for posterior inference and is written in Python2.x. | faststructure is a software package for inferring population structure from large SNP genotype data. It is designed to work efficiently with large datasets and can identify population structure in the presence of admixture. | Population Structure Inference, Analysis Of Large Snp Genotype Data, Ability To Handle Datasets With Admixture | Inference Tool | Population Genetics | Genetics | Population Genetics, Structural Biology, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/faststructure | Anvil: 1.0-Py27 | Population Structure Inference | ||||
fasttree | Aces, Anvil, Expanse | FastTree infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. FastTree can handle alignments with up to a million of sequences in a reasonable amount of time and memory. For large alignments, FastTree is 100-1,000 times faster than PhyML 3.0 or RAxML 7. | FastTree is a tool for inferring approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. FastTree can handle alignments with up to a few thousand sequences and has been designed to make trees with the minimum scale up to 100,000 sequences faster by approximating maximum-likelihood with heuristics. | Inference Of Approximately-Maximum-Likelihood Phylogenetic Trees, Support For Both Nucleotide & Protein Sequences, Efficient Handling Of Alignments With Thousands Of Sequences, Speed Optimization For Large-Scale Datasets | Bioinformatics Tool | Phylogenetics | Bioinformatics | Phylogenetics, Bioinformatics, Computational Biology, Sequence Analysis | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/fasttree Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Aces: 2.1.11 Anvil: 2.1.10, 2.1.11 Expanse: 2.1.10 Faster: 2.1.11 |
Phylogenetic Tree Inference | ||||
fastx_toolkit | Anvil | The FASTX-Toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing. Description Source: http://hannonlab.cshl.edu/fastx_toolkit/ |
The FASTX-Toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing. | The toolkit includes programs to filter, modify, and manipulate short-reads and perform various quality control checks on the FastQ files. | http://hannonlab.cshl.edu/fastx_toolkit/galaxy.html | Pre-Processing Tool | Sciences | Biology | Bioinformatics, Short-Reads, Preprocessing | http://hannonlab.cshl.edu/fastx_toolkit/ | Biological Sciences | http://hannonlab.cshl.edu/fastx_toolkit/commandline.html#fastq_info_example | Anvil: https://www.rcac.purdue.edu/software/fastx_toolkit | Anvil: 0.0.14 | Bioinformatics Tools | |
fastx-toolkit | Anvil, Bridges-2, Expanse | The FASTX-Toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing. Description Source: http://hannonlab.cshl.edu/fastx_toolkit/ |
The fastx-toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing. The tools simplify and streamline various tasks related to quality control, adapter trimming, and format conversion of next-generation sequencing data. | Quality Filtering Of Fastq Files, Adapter Trimming, Format Conversion Between Fasta & Fastq Files, Length Filtering, Sequence Preprocessing | http://hannonlab.cshl.edu/fastx_toolkit/galaxy.html | Tool | Sciences | Biology | Bioinformatics, Ngs Data Processing, Sequence Analysis, Fastq Manipulation | http://hannonlab.cshl.edu/fastx_toolkit/ | Biological Sciences | http://hannonlab.cshl.edu/fastx_toolkit/commandline.html#fastq_info_example | Anvil: https://www.rcac.purdue.edu/software/fastx-toolkit Bridges-2: https://www.psc.edu/resources/software/fastx-toolkit Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 0.0.14 Bridges-2: 0.0.14 Expanse: 0.0.14 |
Data Processing & Analysis | |
fdasrsf | Faster | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.3.12 | |||||||||||||
femzip-l | Faster | femzip-l is a lossless compression tool designed specifically for Finite Element Models (FEM) in engineering and computational sciences. It aims to reduce the storage space required for FEM data without compromising on the accuracy and integrity of the model. | 1. Lossless compression of Finite Element Models (FEM) data.\r 2. Reduction of storage space required for FEM data.\r 3. Maintains the accuracy and integrity of the model throughout the compression process. |
Tool | Computational Sciences | Engineering & Technology | Compression, Finite Element Models, Engineering, Computational Sciences | Engineering & Technology | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 10.73 | Data Compression | |||||
ffmpeg | Aces, Anvil, Bridges-2, Expanse, Faster, Ookami | FFmpeg is a collection of libraries and tools to process multimedia content such as audio, video, subtitles and related metadata. Description Source: https://github.com/FFmpeg/FFmpeg |
FFmpeg is a free and open-source software project consisting of a large suite of libraries and programs for handling video, audio, and other multimedia files and streams. | Encoding, Decoding, Transcoding, Muxing, Demuxing, Streaming, Filtering, & Playing Audio/Video Files, Support For A Wide Range Of Codecs, Formats, & Protocols, Cross-Platform Compatibility | https://www.ffmpeg.org/documentation.html | Tool | Media Processing, Multimedia, Video, Audio | https://www.ffmpeg.org/ | Engineering & Technology | https://trac.ffmpeg.org/wiki/Encode/H.264 https://trac.ffmpeg.org/wiki |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/ffmpeg Bridges-2: https://www.psc.edu/resources/software/ffmpeg Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 4.3.2, 4.4.2, 5.1.2, 6.0 Anvil: 4.2.2 Bridges-2: 4.3.1 Expanse: Vac6D7F, W7Ehiyr Faster: 4.2.2, 4.3.1, 4.3.2, 4.4.2, 5.0.1, 5.1.2, 6.0 Ookami: 5.1 |
Utility | |||
ffnvcodec | Aces, Faster | FFmpeg version of headers required to interface with Nvidias codec APIs. Description Source: https://github.com/FFmpeg/nv-codec-headers |
ffnvcodec is a codec library provided by NVIDIA for efficient video encoding and decoding using the NVIDIA GPU hardware acceleration. | 1. Hardware-accelerated video encoding and decoding with NVIDIA GPUs\r 2. Support for popular video codecs such as H.264 and HEVC\r 3. High-performance video processing\r 4. Integration with NVIDIA CUDA technology for parallel processing |
https://git.videolan.org/?p=ffmpeg/nv-codec-headers.git;a=tree | Library | Codec, Video Processing, Gpu Acceleration | https://git.videolan.org/?p=ffmpeg/nv-codec-headers.git | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 11.1.5.2, 12.0.16.0 Faster: 11.1.5.2, 12.0.16.0 |
Codec Library | ||||
fftw | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Kyric | FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST). We believe that FFTW, which is free software, should become the FFT library of choice for most applications. Description Source: https://www.fftw.org/ |
FFTW is a fast C library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data. It is widely used in areas such as signal processing, data compression, and solving partial differential equations. | 1. Efficient DFT computation in multiple dimensions.\r 2. Supports both real and complex data.\r 3. High performance through optimized algorithms and implementations.\r 4. Portable and easy-to-use interface.\r 5. Scalable to large input sizes. |
https://www.fftw.org/fftw3_doc/ | Computational Software | Numerical Analysis | Applied Mathematics | Signal Processing, Data Compression, Partial Differential Equations | https://www.fftw.org/ | Mathematics | https://www.fftw.org/fftw3_doc/Tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/fftw Bridges-2: https://www.psc.edu/resources/software/fftw Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.3.8, 3.3.9, 3.3.10 Anvil: 2.1.5, 3.3.8 Bridges-2: 3.3.8 Delta: 3.3.10 Expanse: Bmvqsbr, Cesmlwb, ... Faster: 3.3.8, 3.3.9, 3.3.10 |
Library | |
fftw.mpi | Aces, Faster | FFTW.mpi is a part of the FFTW (Fastest Fourier Transform in the West) library that specializes in performing highly efficient, parallel Fast Fourier Transforms (FFTs) using MPI (Message Passing Interface) for distributed-memory computing environments. This extension enables the library to handle large-scale FFT computations across multiple processors in a cluster, optimizing performance for applications in engineering, physics, and other scientific fields that require processing large datasets or complex numerical simulations. | FFTW is a comprehensive collection of fast C routines for computing the Discrete Fourier Transform (DFT) and various generalizations, used in a wide range of applications in computational mathematics, physics, and engineering. | The mpi version of FFTW provides parallel computing capabilities using the Message Passing Interface (MPI) standard, enabling high-performance computations of Fourier transforms across distributed computing resources. This allows for efficient processing of large datasets and complex simulations in parallel. | https://www.fftw.org/fftw3_doc/FFTW-MPI-Reference.html | Tool | Engineering | Computational Software, Hpc Tools | https://www.fftw.org/fftw3_doc/Distributed_002dmemory-FFTW-with-MPI.html#Distributed_002dmemory-FFTW-with-MPI | Mathematics | https://www.fftw.org/fftw3_doc/Using-MPI-Plans.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.3.10 Faster: 3.3.10 |
Computational Mathematics | ||
fftw3 | Ookami, Stampede3 | FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST). We believe that FFTW, which is free software, should become the FFT library of choice for most applications. Description Source: https://www.fftw.org/ |
The Fastest Fourier Transform in the West (FFTW) is an open-source software library for calculating discrete Fourier transforms (DFTs) efficiently. It provides a wide range of algorithms for executing Fourier transforms of various sizes, both real and complex data. | 1. Efficient computation of discrete Fourier transforms (DFTs)\r 2. Support for various transform sizes and data types\r 3. Thread-safe and parallelized algorithms for performance optimization\r 4. Portability across different platforms\r 5. Customizable with user-defined options and configurations |
https://www.fftw.org/fftw3_doc/ | Numerical Library | Computational Physics | Condensed Matter Physics | Fft, Fourier Transform, Open-Source, Computational Physics | https://www.fftw.org/ | Physical Sciences | https://www.fftw.org/fftw3_doc/Tutorial.html | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Ookami: Gcc12/Openmpi4.1.4/3.3.10 Stampede-3: 3.3.10 |
Library | |
fiji | Faster | Fiji is an image processing package, a distribution of ImageJ, bundling a lot of plugins which facilitate scientific image analysis. It is open-source software extensively used in scientific research for image visualization and processing. | Key features of Fiji include a user-friendly interface, support for a wide range of image file formats, a large collection of built-in plugins for image enhancement and analysis, customizable scripting with a macro language, and the ability to create custom plugins. | Analysis Tool | Image Processing, Scientific Research, Image Analysis | Other Natural Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.9.0 | Image Processing Software | |||||||
file | Aces, Faster | The file command is "a file type guesser", that is, a command-line tool that tells you in words what kind of data a file contains. Description Source: https://www.darwinsys.com/file/ |
File is a command-line utility that performs file type identification. It is commonly used to determine the file type and content of a given file or set of files. | Identifying File Types, Determining File Content | https://linux.die.net/man/1/file | Command Line Tool | File Management, Command-Line Utility | https://www.darwinsys.com/file/ | https://man7.org/linux/man-pages/man1/file.1.html#EXAMPLES | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.43 Faster: 5.38, 5.43 |
Utility | ||||
filtlong | Anvil | Filtlong is a tool for filtering long reads by quality. It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter. | filtlong is a tool for filtering long reads generated by third-generation sequencing technologies such as PacBio or Oxford Nanopore. It allows for the removal of reads based on user-defined length or quality thresholds. | Filtering Of Long Reads, Supports Pacbio & Oxford Nanopore Sequencing Data, Option To Specify Length Or Quality Thresholds For Filtering | Data Filtering Tool | Genetics | Biological Sciences | Bioinformatics, Long Read Sequencing, Sequence Data Processing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/filtlong | Anvil: 0.2.1 | Sequence Data Analysis | ||||
fiona | Aces, Faster | Fiona is designed to be simple and dependable. It focuses on reading and writing data in standard Python IO style and relies upon familiar Python types and protocols such as files, dictionaries, mappings, and iterators instead of classes specific to OGR. Fiona can read and write real-world data using multi-layered GIS formats and zipped virtual file systems and integrates readily with other Python GIS packages such as pyproj, Rtree, and Shapely. | Fiona is a Python library for reading and writing geospatial vector data formats. | Support For Various Gis File Formats Such As Shapefile, Geojson, Kml, Gpkg, & Others, Integration With Ogr (Simple Features Library) For Efficient Data Access, Ability To Read & Write Vector Data With Support For Geometry Manipulation, Designed For Easy Interaction With Geospatial Data In Python Applications | Library | Python Library, Geospatial Data, Gis, Vector Data | Earth & Environmental Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.8.21, 1.9.2, 1.9.5 Faster: 1.8.16-Python-3.8.2, 1.8.20, 1.8.21, 1.9.5 |
Data Processing & Visualization | ||||||
firefox | Aces, Faster | Firefox is a free, open source Web browser for Windows, Linux and Mac OS X. | Mozilla Firefox, commonly known as Firefox, is a free and open-source web browser developed by the Mozilla Foundation and its subsidiary, Mozilla Corporation. It is available for Windows, macOS, Linux, and mobile devices. Firefox focuses on privacy, speed, and customization. | Cross-Platform Web Browser, Open-Source Software, Highly Customizable With Add-Ons & Themes, Enhanced Privacy Features Like Tracking Protection, Built-In Password Manager & Popup Blocker, Frequent Updates For Security & Performance Improvements | https://developer.mozilla.org/en-US/docs/Mozilla/Firefox | Web Browser | Web Browser, Internet, Privacy, Open-Source, Cross-Platform | https://www.mozilla.org/en-US/firefox/new/ | Computer & Information Sciences | https://developer.mozilla.org/en-US/docs/Learn | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 118.0.2, 124.0.1 Faster: 44.0.2, 114.0B9, 118.0.2 |
Web Browser | |||
firestarter | Faster | Firestarter is a visual firewall tool that allows users to configure a firewall for Linux systems using an easy-to-use graphical interface. It provides a user-friendly way to manage network security policies and rules. | Graphical Interface For Managing Firewall Settings, Ability To Set Up Rules For Incoming & Outgoing Traffic, Monitoring Of Network Connections, Support For Nat Configurations, Logging & Reporting Features | Security Tool | Firewall, Network Security, Linux | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2.0 | Firewall Configuration Tool | |||||||
flac | Aces, Faster | FLAC stands for Free Lossless Audio Codec, an audio format similar to MP3, but lossless, meaning that audio is compressed in FLAC without any loss in quality. Description Source: https://xiph.org/flac/ |
Free Lossless Audio Codec (FLAC) is an open-source audio coding format for lossless compression of digital audio. It offers high audio quality and smaller file sizes without losing any information during compression and decompression. | Lossless compression of audio files, preservation of original audio quality, support for metadata tagging, seeking, and error detection | https://xiph.org/flac/api/index.html | Compression Tool | Audio Codec, Open-Source, Lossless Compression | https://xiph.org/flac/ | Other Computer & Information Sciences | https://github.com/xiph/flac/tree/master/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.3.3, 1.3.4, 1.4.2 Faster: 1.3.3, 1.3.4, 1.4.2 |
Audio Processing | |||
flash | Bridges-2, Faster | FLASH (Fast Length Adjustment of SHort reads) is a very fast and accurate software tool to merge paired-end reads from next-generation sequencing experiments. FLASH is designed to merge pairs of reads when the original DNA fragments are shorter than twice the length of reads. The resulting longer reads can significantly improve genome assemblies. They can also improve transcriptome assembly when FLASH is used to merge RNA-seq data. Description Source: https://ccb.jhu.edu/software/FLASH/ |
Flash is a multi-purpose computational software that specializes in numerical simulations for fluid dynamics, electromagnetics, structural analysis, and other physics-based applications. It is developed and maintained by the Center for Computational Sciences and Engineering at Lawrence Berkeley National Laboratory. | Flash provides a comprehensive suite of tools for solving complex partial differential equations, supporting various physical models and simulation methodologies. It offers advanced meshing capabilities, parallel computing support, visualization tools, and post-processing features. | https://sourceforge.net/p/flashpage/code/ci/master/tree/ | Computational Physics | Fluid & Plasma Physics | Physical Sciences | Computational Software, Numerical Simulation, Fluid Dynamics, Electromagnetics, Structural Analysis | https://ccb.jhu.edu/software/FLASH/ | Physical Sciences | https://sourceforge.net/p/flashpage/code/ci/master/tree/flash.c | Bridges-2: https://www.psc.edu/resources/software/flash Faster: https://hprc.tamu.edu/software/faster/ |
Bridges-2: 1.2.11 Faster: 2.2.00 |
Simulation Software | |
flask | Aces, Faster | Flask is a lightweight WSGI web application framework. It is designed to make getting started quick and easy, with the ability to scale up to complex applications. Description Source: https://palletsprojects.com/p/flask/ |
Flask is a lightweight and versatile Python web application framework that provides the essentials for building web applications. It is known for its simplicity, flexibility, and ease of use, making it a popular choice for developers. | Quick & Easy To Set Up & Get Started, Minimalistic Design With A Simple & Straightforward Api, Extensible Through A Variety Of Plugins & Extensions, Built-In Development Server & Debugger, Support For Secure Cookies & Sessions, Jinja2 Template Engine For Efficient Html Rendering, Werkzeug Wsgi Toolkit For Handling Requests & Responses | https://flask.palletsprojects.com/en/3.0.x/ | Open Source | Web Development, Python, Framework, Web Applications | https://palletsprojects.com/p/flask/ | Computer & Information Sciences | https://flask.palletsprojects.com/en/3.0.x/tutorial/ https://www.tutorialspoint.com/flask/index.htm https://www.fullstackpython.com/flask.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.1.2, 2.2.2 Faster: 1.1.2, 2.0.2, 2.2.2 |
Web Framework | |||
flatbuffers | Aces, Faster | FlatBuffers is a cross platform serialization library architected for maximum memory efficiency. It allows you to directly access serialized data without parsing/unpacking it first, while still having great forwards/backwards compatibility. Description Source: https://github.com/google/flatbuffers/ |
FlatBuffers is an open-source, cross-platform serialization library for efficient data storage and communication. It allows for storing and accessing serialized data without parsing and generating overhead, making it faster and more memory-efficient than traditional serialization methods. | Efficient Data Serialization & Deserialization, Cross-Platform Support, Customizable Data Schemas, Random Access To Serialized Data, Minimal Memory Allocation & Copying | https://flatbuffers.dev/modules.html | Library | Serialization, Data Storage, Communication, Efficiency, Cross-Platform | https://github.com/google/flatbuffers | Computer & Information Sciences | https://flatbuffers.dev/flatbuffers_guide_tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.12.0, 2.0.0, 2.0.7, 23.1.4, 23.5.26 Faster: 1.12.0, 2.0.0, 2.0.7, 23.1.4 |
Serialization Library | |||
flatbuffers-python | Aces, Faster | FlatBuffers is a cross platform serialization library architected for maximum memory efficiency. It allows you to directly access serialized data without parsing/unpacking it first, while still having great forwards/backwards compatibility. Description Source: https://github.com/google/flatbuffers/ |
https://flatbuffers.dev/flatbuffers_guide_use_python.html | Library | https://pypi.org/project/flatbuffers/ | https://github.com/google/flatbuffers/blob/master/samples/sample_binary.py https://flatbuffers.dev/flatbuffers_guide_tutorial.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.12, 2.0, 23.1.4, 23.5.26 Faster: 1.12, 2.0, 23.1.4 |
||||||||
flex | Aces, Faster, Ookami | flex (fast lexical analyzer generator) is a tool for generating scanners: programs which recognize lexical patterns in text. Description Source: https://github.com/westes/flex |
Flex is a fast lexical analyzer generator. It is a tool for creating programs that perform pattern-matching on text. It reads the given input files for a description of a scanner to generate and produces a C source file for the scanner. The output file, lex.yy.c, can then be compiled and linked with the flex runtime library to produce an executable. The resulting executable will scan input files for occurrences of the regular expressions in the scanner description, and perform actions specified in the description. | 1. Generates C source code for lexical analyzers based on specified patterns.\r 2. Provides a fast and efficient tool for performing text pattern matching.\r 3. Offers flexibility in defining scanner descriptions using regular expressions and associated actions.\r 4. Supports the development of scanners for use in various text processing applications. |
https://westes.github.io/flex/manual/ | Lexical Analyzer, Text Processing, Pattern Matching, Scanner Generator | https://github.com/westes/flex | http://alumni.cs.ucr.edu/~lgao/teaching/flex.html https://westes.github.io/flex/manual/Common-Patterns.html#Common-Patterns |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 2.6.4 Faster: 2.6.3, 2.6.4 Ookami: 2.6.4 |
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flexiblas | Aces, Delta, Faster | FlexiBLAS is a wrapper library that enables the exchange of the BLAS and LAPACK implementation used by a program without recompiling or relinking it. Description Source: https://gitlab.mpi-magdeburg.mpg.de/software/flexiblas-release |
FlexiBLAS is a lightweight BLAS (Basic Linear Algebra Subprograms) library that aims to provide efficient and flexible implementations of BLAS routines for various hardware platforms. It is designed to optimize performance on CPUs, GPUs, and other accelerators, making it suitable for a wide range of scientific computing applications. | Efficient Implementations Of Blas Routines, Support For Various Hardware Platforms Including Cpus, Gpus, & Accelerators, High Performance Optimization Techniques, Lightweight & Easy To Use | https://gitlab.mpi-magdeburg.mpg.de/software/flexiblas-release#documentation | Library | Blas Library, Scientific Computing, Linear Algebra | https://www.mpi-magdeburg.mpg.de/projects/flexiblas | Other Mathematics | https://gitlab.mpi-magdeburg.mpg.de/software/flexiblas-release/-/tree/master/examples?ref_type=heads | Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.0.4, 3.2.0, 3.2.1, 3.3.1 Delta: 3.3.0 Faster: 3.0.4, 3.2.0, 3.2.1, 3.3.1 |
Computational Software | |||
flit | Aces, Faster | A simple packaging tool for simple packages. | Flit is a simple tool for building and distributing Python packages. | Building Python Packages, Distributing Python Packages | Building & Distribution Tool | Python Packaging, Package Management | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.9.0 Faster: 3.9.0 |
Package Management Tool | ||||||
fltk | Aces, Faster | FLTK is a cross-platform C++ GUI toolkit for UNIX®/Linux® (X11), Microsoft® Windows®, and macOS®. FLTK provides modern GUI functionality without the bloat and supports 3D graphics via OpenGL® and its built-in GLUT emulation. Description Source: https://www.fltk.org/ |
FLTK (Fast, Light Toolkit) is a cross-platform C++ GUI toolkit for developing graphical user interfaces. It provides various widgets and tools for creating interactive and responsive graphical applications. | Cross-Platform Gui Development, Multiple Widgets For Building Interfaces, Event Handling & Callback Functionality, Support For Opengl Integration, Lightweight & Fast Performance | https://fltk.gitlab.io/fltk/ | Development Tool | Gui Toolkit, Cross-Platform Development, C++ Library | https://www.fltk.org/ | Engineering & Technology | https://fltk.gitlab.io/fltk/basics.html https://fltk.gitlab.io/fltk/examples.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.3.8 Faster: 1.3.5, 1.3.7, 1.3.8 |
Cross-Platform Gui Library | |||
flye | Anvil | Flye: Fast and accurate de novo assembler for single molecule sequencing reads | Flye is a long-read assembler designed to assemble genomes using nanopore sequencing data. It aims to provide accurate and high-quality genome assemblies by utilizing long reads. | 1. Long-read assembly 2. Utilizes nanopore sequencing data 3. Accurate genome assemblies 4. High-quality output | Bioinformatics Tool | Genome Assembly & Analysis | Genomics | Genome Assembly, Long-Read Sequencing, Nanopore Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/flye | Anvil: 2.9, 2.9.1, 2.9.2 | Assembly | ||||
fms2 | Ookami | fms2 is an efficient and flexible Fortran to C++ source-to-source compiler that aids in translating Fortran 77/90/95 code to modern C++ code, enabling improved performance and compatibility. | fms2 offers automatic translation of legacy Fortran code to modern C++ for enhanced performance, supports Fortran 77/90/95 standards, assists in porting legacy scientific applications to modern architectures, provides optimizations for improved computational efficiency. | https://noaa-gfdl.github.io/FMS/ | Source-To-Source Compiler | Compiler, Software, Translation | https://github.com/NOAA-GFDL/FMS | Other Computer & Information Sciences | https://noaa-gfdl.github.io/FMS/autotools.html https://noaa-gfdl.github.io/FMS/cmake.html https://noaa-gfdl.github.io/FMS/md_TESTING.html |
Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: Gcc12.1.0/2022.04 | Compiler | ||||
foldseek | Faster | FoldSeek is a Python package for predicting RNA secondary structures using deep learning models. It utilizes Convolutional Neural Networks (CNNs) to learn the complex patterns in RNA sequences and predict the secondary structures. | Prediction Of RNA Secondary Structures, Utilizes Deep Learning Models, Specifically Cnns, Python-Based Package, Allows For Training Custom Models | Library | Bioinformatics | Biological Sciences | RNA Secondary Structure Prediction, Deep Learning Models, Python Package | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3-915Ef7D-Linux64-Avx2 | Computational Biology | |||||
fontconfig | Aces, Faster | Fontconfig is a library for configuring and customizing font access. Description Source: https://www.freedesktop.org/wiki/Software/fontconfig/ |
Fontconfig is a library designed to provide system-wide font configuration, customization, and management for user interfaces and text display on Linux and other Unix-like operating systems. It allows applications to discover and access fonts, and provides settings for font selection, aliasing, subsetting, and caching. | System-Wide Font Configuration, Font Discovery & Access For Applications, Font Aliasing & Subsetting, Font Caching For Performance Optimization | https://fontconfig.pages.freedesktop.org/fontconfig/fontconfig-user.html | System Tool | Fontconfig, Font Management, Font Configuration, Linux, Unix-Like Systems | https://www.freedesktop.org/wiki/Software/fontconfig/ | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.13.92, 2.13.93, 2.13.94, 2.14.0, 2.14.1, 2.14.2 Faster: 2.13.1, 2.13.92, 2.13.93, 2.13.94, 2.14.0, 2.14.1, 2.14.2 |
Library | ||||
formats | Faster | Faster: https://hprc.tamu.edu/software/faster/ | ||||||||||||||
foss | Aces, Faster | The foss common compiler toolchain consists entirely of open source software (hence the name, derived from the common term 'FOSS', which is short for "Free and Open Source Software"). Description Source: https://docs.easybuild.io/common-toolchains/#common_toolchains_foss |
FOSS (Free and Open Source Software) refers to software that is both free to use and distribute, as well as with access to the source code for modification or enhancement by users. | 1. Free for distribution and modification. 2. Access to the source code for transparency and customization. 3. Collaboration and community-driven development. 4. Cost-effective and sustainable solutions. 5. Promotes innovation and knowledge sharing. | https://docs.easybuild.io/common-toolchains/#common_toolchains_foss | Software Library | Free Software, Open Source Software, Software Development | https://docs.easybuild.io/common-toolchains/#common_toolchains_foss | Other Computer & Information Sciences | https://docs.easybuild.io/version-specific/toolchain-opts/#foss | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2020B, 2021A, 2021B, 2022A, 2022B, 2023A, 2023B, 2023.09 Faster: 2018B, 2019B, 2020A, 2020B, 2021A, 2021B, 2022A, 2022B, 2023A, 2023B |
Development Tools | |||
fosscuda | Aces, Faster | fosscuda is a compiler toolchain with GCC+CUDA, OpenMPI, OpenBLAS, ScaLAPACK and FFTW. Description Source: https://docs.easybuild.io/api/easybuild/toolchains/fosscuda/?h=fosscuda |
FOSSCUDA stands for Free and Open-Source Software for CUDA (Compute Unified Device Architecture) and is a collection of tools and libraries that enable developers to leverage the power of NVIDIA GPUs for parallel computing tasks. | 1. Provides open-source alternatives to proprietary CUDA tools. 2. Enables accelerated computing on NVIDIA GPUs. 3. Supports parallel processing and high-performance computing applications. 4. Includes libraries and frameworks for GPU-accelerated programming. | https://docs.easybuild.io/common-toolchains/#common_toolchains_foss | Compiler/Library | Artificial Intelligence & Intelligent Systems | Computer Science | Cuda, Gpu Computing, Parallel Programming, Open-Source | https://docs.easybuild.io/common-toolchains/#common_toolchains_foss | Computer & Information Sciences | https://docs.easybuild.io/version-specific/toolchain-opts/#fosscuda | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2020B Faster: 2019B, 2020A, 2020B |
Software Development/Tools | |
fq | Anvil | Fq is a command line utility for manipulating Illumina-generated FastQ files. | fq is a command-line tool for filtering and manipulating FASTQ files, which are used to store biological sequences and their quality scores obtained from high-throughput sequencing. It provides functionalities for filtering reads based on quality scores, length, and other criteria, as well as for modifying read headers and sequences. | Filtering Fastq Files Based On Quality Scores, Filtering Reads Based On Length, Modifying Read Headers & Sequences, Command-Line Interface For Easy Usage | Command-Line Tool | Fastq File Manipulation, High-Throughput Sequencing Data Processing, Biological Sequence Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fq | Anvil: 0.10.0 | Bioinformatics Tool | ||||||
fraggenescan | Anvil | Fraggenescan is an application for finding (fragmented) genes in short reads. It can also be applied to predict prokaryotic genes in incomplete assemblies or complete genomes. | FragGeneScan is a gene-finding program specifically designed for short reads from next-generation sequencing (NGS) technology. It predicts protein-coding sequences in short DNA sequences such as metagenomic and single-cell sequencing data. | 1. Prediction Of Protein-Coding Sequences, 2. Designed For Short Reads From Ngs Technology, 3. Particularly Useful For Metagenomic & Single-Cell Sequencing Data, 4. Supports Both Metagenomic & Whole Genome Sequencing Data | Bioinformatics | Genetics | Biological Sciences | Gene Prediction, Ngs Data Analysis, Metagenomics, Single-Cell Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fraggenescan | Anvil: 1.31 | Gene Prediction | ||||
fraggenescanrs | Anvil | FragGeneScanRs is a better and faster Rust implementation of the FragGeneScan gene prediction model for short and error-prone reads. | FragGeneScanRS is a robust tool for gene prediction in metagenomes and fragmented assemblies, specifically designed to accurately predict protein-coding genes in short reads and incomplete assemblies. | Accurate Gene Prediction In Metagenomic Data, Suitable For Short Reads & Fragmented Assemblies, Improved Performance In Predicting Protein-Coding Genes, Support For Various Input Formats | Tool | Bioinformatics | Biological Sciences | Gene Prediction, Metagenomics, Fragmented Assemblies | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fraggenescanrs | Anvil: 1.1.0 | Bioinformatics | ||||
freebayes | Anvil, Faster | Freebayes is a Bayesian genetic variant detector designed to find small polymorphisms, specifically SNPs (single-nucleotide polymorphisms), indels (insertions and deletions), MNPs (multi-nucleotide polymorphisms), and complex events (composite insertion and substitution events) smaller than the length of a short-read sequencing alignment. | FreeBayes is a Bayesian genetic variant detector designed to find small polymorphisms, specifically SNPs (single-nucleotide polymorphisms), indels (insertions and deletions), and complex events (composite insertion and substitution events) smaller than the length of a short-read sequencing alignment. | Detection Of Small Polymorphisms Including Snps, Indels, & Complex Events, Designed For Short-Read Sequencing Data, Utilizes A Bayesian Algorithm For Variant Detection | Tool | Genomics | Bioinformatics | Genetic Variant Detector, Snp Detection, Indel Detection, Bayesian Algorithm | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/freebayes Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 1.3.5, 1.3.6 Faster: 1.3.4-Linux-Static-Amd64 |
Genomic Variant Calling Tool | ||||
freeglut | Aces, Faster | freeglut is a free-software/open-source alternative to the OpenGL Utility Toolkit (GLUT) library. GLUT (and hence freeglut) takes care of all the system-specific chores required for creating windows, initializing OpenGL contexts, and handling input events, to allow for trully portable OpenGL programs. Description Source: https://freeglut.sourceforge.net/ |
FreeGLUT is a free-software/open-source alternative to the OpenGL Utility Toolkit (GLUT) library. It provides a simple, platform-independent API for creating windows, sub-windows, and menus, as well as handling input from keyboard, mouse, and joystick devices. FreeGLUT aims to be as close to the original GLUT functionality as possible while also improving and extending it. | Cross-Platform Support, Window Management, User Input Handling, Event-Driven Programming, Opengl Integration | https://freeglut.sourceforge.net/docs/api.php | Graphics Library | Graphics Programming, Opengl, Cross-Platform Development, Free Software | https://freeglut.sourceforge.net/ | Computer & Information Sciences | https://github.com/freeglut/freeglut/blob/master/README.cmake | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.2.1, 3.2.2, 3.4.0 Faster: 3.2.1, 3.2.2 |
Libraries | |||
freeimage | Faster | FreeImage is an open-source graphics library that supports popular image formats and features image loading, saving, conversion, manipulation, and processing capabilities. | Support For Various Image Formats Including Bmp, Gif, Png, Jpeg, Tiff, & More, Image Loading & Saving Functionality, Image Conversion & Manipulation Tools, High-Quality Image Processing Algorithms, Suitable For Use In Graphics, Digital Photography, Medical Imaging, & Other Applications | Graphics Library | Graphics Library, Image Processing, Open-Source | Engineering & Technology | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.18.0 | Library | |||||||
freeipmi | Ookami | FreeIPMI provides in-band and out-of-band IPMI software based on the IPMI v1.5/2.0 specification. The IPMI specification defines a set of interfaces for platform management and is implemented by a number of vendors for system management. The features of IPMI that most users will be interested in are sensor monitoring, system event monitoring, power control, and serial-over-LAN (SOL). Description Source: https://www.gnu.org/software/freeipmi/ |
FreeIPMI is an open-source BMC (Baseboard Management Controller) software that provides a consistent and reliable interface for managing and monitoring IPMI-compliant systems. It allows administrators to remotely manage server hardware, monitor sensors, power on/off servers, and perform other BMC-related functions. | Remote Power Control, Sensor Monitoring, System Event Log Retrieval, Fru Data Retrieval, Health Monitoring | https://www.gnu.org/software/freeipmi/documentation.html | Management & Monitoring Tool | Bmc, Baseboard Management Controller, Open-Source, Hardware Management, Monitoring | https://www.gnu.org/software/freeipmi/index.html | Computer & Information Sciences | https://www.gnu.org/software/freeipmi/README.build https://www.gnu.org/software/freeipmi/freeipmi-hostrange.txt |
Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 1.6.4 | Systems Software | |||
freesurfer | Expanse | FreeSurfer is a software suite used for the analysis and visualization of structural and functional neuroimaging data from MRI and CT scans. It is widely used in the field of neuroscience and neuroimaging research. | Automatic Segmentation Of Brain Mri Data, Cortical Surface Reconstruction, Volume Measurements Of Brain Structures, Functional Mri Analysis Tools, Visualization Of Neuroimaging Data | Scientific | Neuroimaging | Neuroscience | Neuroimaging, Mri Analysis, Brain Segmentation, Functional Mri, Image Visualization | Biological Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 7.1.1, 7.2.0 | Imaging Analysis | |||||
freetype | Aces, Faster | FreeType is a freely available software library to render fonts. Description Source: https://freetype.org/ |
FreeType is a software font engine that is designed to be small, efficient, highly customizable, and portable while capable of producing high-quality output (glyph images). It can be used in various applications that require text rendering, such as operating systems, web browsers, desktop publishing tools, and more. | 1. Support for several font formats including TrueType, OpenType, Type 1, and CID-keyed fonts.\r 2. Efficient rendering of high-quality glyph images.\r 3. Ability to hint fonts to improve rendering at small sizes.\r 4. Comprehensive API for developers to integrate font handling and rendering into their applications.\r 5. Portable across different platforms such as Windows, macOS, Linux, and more. |
https://freetype.org/freetype2/docs/reference/index.html | Font Engine | Font Engine, Text Rendering, Typography | https://freetype.org/ | Computer & Information Sciences | https://freetype.org/freetype2/docs/tutorial/index.html https://freetype.org/freetype2/docs/tutorial/step3.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.10.3, 2.10.4, 2.11.0, 2.12.1, 2.13.0 Faster: 2.10.1, 2.10.3, 2.10.4, 2.11.0, 2.12.1, 2.13.0 |
Operating System/Graphic Library | |||
freexl | Aces, Faster | FreeXL is an open source library to extract valid data from within an Excel (.xls) spreadsheet. | FreeXL is a library to extract data from Excel (.xls) spreadsheet files. The library allows for reading Excel files without the need for Microsoft Excel to be installed. | 1. Reading data from Excel (.xls) files\r 2. No dependency on Microsoft Excel\r 3. Cross-platform compatibility\r 4. Simple API for easy integration into other projects |
Data Extraction | Excel, Spreadsheet, Data Extraction | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.0.6 Faster: 1.0.6 |
Library | ||||||
freyja | Anvil | Freyja is a tool to recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset. | Freyja is a software tool designed for computational chemistry and quantum mechanics calculations. It provides a range of functionalities to simulate and analyze molecular systems. | Molecular Dynamics Simulations, Quantum Mechanical Calculations, Energy Minimization, Molecular Structure Optimization, Visualization Of Molecular Systems | Molecular Modeling | Chemical Sciences | Physical Sciences | Computational Chemistry, Quantum Mechanics, Molecular Simulations, Molecular Modeling, Chemistry Software | Chemical Sciences | Anvil: https://www.rcac.purdue.edu/software/freyja | Anvil: 1.3.11, 1.4.2 | Computational Software | ||||
fribidi | Aces, Faster, Ookami | The Free Implementation of the Unicode Bidirectional Algorithm. Description Source: https://github.com/fribidi/fribidi?tab=readme-ov-file |
GNU FriBidi is an implementation of the Unicode Bidirectional Algorithm (bidi). It also provides utility functions to help work with bidirectional text. | Implementation Of The Unicode Bidirectional Algorithm, Utility Functions For Working With Bidirectional Text | https://github.com/fribidi/fribidi?tab=readme-ov-file#api | Text Processing | Unicode, Bidirectional Algorithm | https://github.com/fribidi/fribidi | Computer & Information Sciences | https://github.com/fribidi/fribidi/tree/master/test | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 1.0.10, 1.0.12 Faster: 1.0.5, 1.0.9, 1.0.10, 1.0.12 Ookami: 1.0.13 |
Library | |||
fseq | Anvil | Fseq is a feature density estimator for high-throughput sequence tags | F-seq is a Python package that provides tools for peak calling and peak detection in functional genomics datasets, specifically ChIP-seq and DNase-seq data. It is designed to identify enriched regions in the genome that represent potential binding sites of proteins or other functional elements. | Peak Calling In Chip-Seq & DNAse-Seq Data, Identification Of Enriched Regions In The Genome, Analysis Of Potential Binding Sites Of Proteins Or Functional Elements | Python Library | Functional Genomics | Genomics | Genomics, Peak Calling, Functional Genomics, Python Package | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fseq | Anvil: 2.0.3 | Bioinformatics | ||||
fsl | Faster | FSL (FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural, and diffusion MRI brain imaging data. It provides various image processing tools to process and analyze data acquired using MRI techniques. | Some core features of FSL include preprocessing of MRI data for better analysis, registration of images to a standard space, statistical analysis of MRI data, and tools for brain segmentation and visualization. | Image Processing Software | Biophysics, Neuroscience | Biological Sciences | Mri, Imaging, Neuroimaging, Data Analysis, Image Processing | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 6.0.5-Slurm | Medical Imaging Software | |||||
ftp | Anvil | A File Transfer Protocol client (FTP client) is a software utility that establishes a connection between a host computer and a remote server, typically an FTP server. | FTP (File Transfer Protocol) is a standard network protocol used for the transfer of computer files between a client and server on a computer network. It allows users to upload or download files and directories, as well as perform other file operations such as renaming, deleting, and creating directories. | File Transfer Between Client & Server, Upload & Download Files & Directories, Rename, Delete, & Create Directories, Authentication & Security Features | Tool | Network Protocol, File Transfer, Client-Server Communication | Anvil: https://www.rcac.purdue.edu/software/ftp | Anvil: 0.17 | Networking & Communication | |||||||
fujitsu | Ookami | Fujitsu is a multinational information technology equipment and services company headquartered in Tokyo, Japan. Fujitsu offers a wide range of products and services including servers, storage systems, software, networking equipment, and more. | Fujitsu provides innovative solutions in the areas of cloud computing, big data analytics, artificial intelligence, IoT, and cybersecurity. Their products and services cater to various industries including finance, healthcare, retail, and manufacturing. | https://software.fujitsu.com/jp/manual/manualindex/p22000026e.html | It Services, Information Technology, Hardware, Software | https://www.fujitsu.com/emeia/products/computing/servers/mainframe/bs2000/software/programming/cpp.html | Computer & Information Sciences | https://www.stonybrook.edu/commcms/ookami/support/faq/ookami-fujitsu-compilers https://software.fujitsu.com/jp/manual/manualfiles/m200007/j2ul2578/02enz000/j2ul-2578-02enz0.pdf |
Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | |||||||
funannotate | Anvil, Bridges-2 | Funannotate is a genome prediction, annotation, and comparison software package. It was originally written to annotate fungal genomes (small eukaryotes ~ 30 Mb genomes), but has evolved over time to accomodate larger genomes. Description Source: https://funannotate.readthedocs.io/en/latest/# |
funannotate is a pipeline for genome prediction and annotation of fungi. It automates the process of predicting gene models, functional annotation, and comparative genomics analysis for fungal genomes. | Automated Genome Prediction & Annotation For Fungi, Gene Model Prediction Using Multiple Tools, Functional Annotation With Interproscan, Signalp, & Other Databases, Comparative Genomics Analysis For Multiple Genomes, User-Friendly Interface For Customization & Visualization | https://funannotate.readthedocs.io/en/latest/ | Bioinformatics Tool | Genetics | Biological Sciences | Genome Prediction, Genome Annotation, Fungi, Bioinformatics | https://github.com/nextgenusfs/funannotate | Biological Sciences | https://funannotate.readthedocs.io/en/latest/tutorials.html | Anvil: https://www.rcac.purdue.edu/software/funannotate Bridges-2: https://www.psc.edu/resources/software/funannotate |
Anvil: 1.8.10, 1.8.13 Bridges-2: 1.8.9 |
Genome Annotation | |
futhark | Faster | Futhark is a purely functional data-parallel programming language that aims to make high-performance GPU programming approachable to a wider audience. It is designed for efficiently running complex computations on modern GPUs. | Purely Functional Programming Language, Data-Parallel Programming Model, Designed For Gpu Programming, High-Performance Computing Capabilities | Compiler | Programming Language, Data-Parallel Programming, Gpu Programming, High-Performance Computing | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.19.5 | Programming Language | |||||||
fwdpy11 | Anvil | Fwdpy11 is a Python package for forward-time population genetic simulation. | fwdpy11 is a flexible and efficient Python library for forward-time population genetics simulations. It provides tools for simulating a wide range of evolutionary scenarios and analyzing the resulting genetic data. | Simulation Of Genetic Drift, Forward-Time Population Genetics Modeling, Genetic Data Analysis Tools, Support For Various Evolutionary Scenarios, Efficient & Flexible Simulation Capabilities | Python Library | Population Genetics | Biological Sciences | Population Genetics, Genetic Simulation, Python Library, Genetic Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/fwdpy11 | Anvil: 0.18.1 | Simulation Tool | ||||
g2clib | Aces, Faster | Library contains GRIB2 encoder/decoder ('C' version). | g2clib is a library for the manipulation of geophysical data in the GEMPAK format. It provides routines for reading, writing, and manipulating meteorological and geophysical data. | 1. Reading and writing GEMPAK files\r 2. Geophysical data manipulation\r 3. Support for meteorological data\r 4. Data analysis and visualization functions |
Computational Tool | Geophysics, Meteorology, Data Manipulation, Data Analysis | Earth & Environmental Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.6.3 Faster: 1.6.0 |
Library | ||||||
g2lib | Aces | Library contains GRIB2 encoder/decoder and search/indexing routines. | g2lib is a C++ library for 2D and 3D geometric computing, mainly focusing on computational geometry and computer graphics. It provides efficient and robust geometric algorithms for various tasks. | 1. Robust geometric algorithms for intersection testing, distance computation, convex hulls, triangulation, Voronoi diagrams, etc.\r 2. Support for both 2D and 3D geometric operations.\r 3. Implementation of algorithms like line-line intersection, point location, closest point on a segment, and more.\r 4. Suitable for applications in computer graphics, visualization, spatial analysis, and geometric modeling. |
Computational Software | Computational Geometry, Computer Graphics, Geometric Computing | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 3.2.0 | Library | ||||||
gadma | Anvil | GADMA is a command-line tool. Basic pipeline presents a series of launches of the genetic algorithm folowed by local search optimization and infers demographic history from the Allele Frequency Spectrum of multiple populations. | GADMA (Genetic Algorithm for Detecting Mutually exclusive Alterations) is a tool for identifying mutually exclusive alterations in cancer using a genetic algorithm approach. | 1. Utilizes genetic algorithm techniques for identifying mutually exclusive alterations. 2. Provides visualization tools for results interpretation. 3. Supports input data from various cancer genomics studies. 4. Allows customization of parameters to refine analysis. 5. Facilitates the discovery of potential driver genes in cancer. | Tool | Genetics | Biological Sciences | Genetic Algorithm, Cancer Genomics, Mutually Exclusive Alterations, Driver Genes | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gadma | Anvil: 2.0.0Rc21 | Bioinformatics | ||||
gambit | Anvil | GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking) is a tool for rapid taxonomic identification of microbial pathogens. | Gambit is an open-source software package for carrying out computational game theory analysis. It provides tools for the representation, numerical solution, and strategic analysis of games, including extensive support for the computation of Nash equilibria. | 1. Representation of games in extensive and strategic form\r 2. Computation of Nash equilibria and other solution concepts\r 3. Analysis of strategic interaction and decision-making\r 4. Visualization of game theoretic solutions\r 5. Support for various game types and player settings |
Software Package | Game Theory | Economics & Business | Game Theory, Computational Analysis, Nash Equilibria | Social Sciences | Anvil: https://www.rcac.purdue.edu/software/gambit | Anvil: 0.5.0 Ookami: 4.9.5 |
Computational Game Theory Tool | ||||
gamess | Bridges-2, Expanse | GAMESS (General Atomic and Molecular Electronic Structure System) is used for ab initio quantum chemistry calculations. It provides a wide range of methods for studying molecular systems, including ground state energies, molecular geometry optimization, and electronic properties, making it a valuable tool for researchers in chemistry and physics. | The General Atomic and Molecular Electronic Structure System (GAMESS) is a suite of ab initio quantum chemistry programs designed for electronic structure calculations of molecules and molecular reactions. It provides a wide range of methods for both molecules and periodic solids. | GAMESS offers an extensive variety of quantum chemistry methods, including Hartree-Fock, density functional theory (DFT), Moller-Plesset perturbation theory, configuration interaction, coupled cluster, and more. It also supports a variety of basis sets, including Gaussian basis functions and Slater-type basis sets. GAMESS is highly configurable and enables users to perform geometry optimizations, vibrational frequency calculations, transition state searches, and other advanced electronic structure calculations. | https://www.msg.chem.iastate.edu/gamess/documentation.html | Quantum Chemistry | Chemical Sciences | Physical Sciences | Quantum Chemistry, Electronic Structure Calculations, Ab Initio Calculations | https://www.msg.chem.iastate.edu/gamess/index.html | Chemical Sciences | https://www.msg.chem.iastate.edu/tutorials/tutorials.html | Bridges-2: https://www.psc.edu/resources/software/gamess Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Bridges-2: 2020 Expanse: Eo5Efva Stampede-3: 2023.06.30 |
Computational Software | |
gamma | Anvil | GAMMA (Gene Allele Mutation Microbial Assessment) is a command line tool that finds gene matches in microbial genomic data using protein coding (rather than nucleotide) identity, and then translates and annotates the match by providing the type (i.e., mutant, truncation, etc.) | Gamma is a software package for probabilistic modeling, Bayesian inference, and statistical analysis. It provides tools for fitting complex models to data, performing parameter estimation, and uncertainty quantification. | 1. Probabilistic modeling\r 2. Bayesian inference\r 3. Statistical analysis\r 4. Parameter estimation\r 5. Uncertainty quantification |
Library | Statistics & Probability | Probabilistic Modeling, Bayesian Inference, Statistical Analysis | Mathematics | Anvil: https://www.rcac.purdue.edu/software/gamma | Anvil: 1.4, 2.2 | Computational Software | |||||
gangstr | Anvil | GangSTR is a tool for genome-wide profiling tandem repeats from short reads. | GangSTR is a tool for profiling short tandem repeats (STRs) from high-throughput sequencing data. It is specifically designed for examining STR variation in whole-genome sequencing data and is optimized for population-scale studies, allowing for accurate STR genotyping and discovery. | 1. Genotyping and discovery of short tandem repeats (STRs) from sequencing data\r 2. Optimized for whole-genome sequencing data\r 3. Designed for population-scale studies\r 4. Accurate detection of STR variation |
Genomic Analysis Tool | Population Genetics | Genomics | Str, Genotyping, Short Tandem Repeats, Sequencing Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gangstr | Anvil: 2.5.0 | Bioinformatics Tool | ||||
gapfiller | Anvil | GapFiller is a seed-and-extend local assembler to fill the gap within paired reads. | GapFiller is a software tool designed for closing gaps and improving genome assemblies by utilizing paired-end reads. It works by enabling the precise elucidation of gaps that occur during the sequencing and assembly process, ultimately enhancing the accuracy and completeness of the assembled genome. | Utilizes Paired-End Reads For Gap Filling, Improves Genome Assembly Accuracy, Enhances Assembly Completeness, Provides Detailed Elucidation Of Sequencing Gaps | Computational Tool | Genomics | Bioinformatics | Genome Assembly, Bioinformatics, Sequencing, Gap Filling | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gapfiller | Anvil: 2.1.2 | Genome Assembly | ||||
gapit | Anvil | GAPIT is a Genome Association and Prediction Integrated Tool. | GAPIT (Genome Association and Prediction Integrated Tool) is a comprehensive software package developed for genome-wide association studies (GWAS) and genomic prediction in crops. It provides a user-friendly interface to perform various statistical analyses and data visualization related to genetic studies in plants. | Conduct Genome-Wide Association Studies (Gwas), Perform Genomic Prediction, Supports A Variety Of Statistical Models, Data Visualization Tools, User-Friendly Interface | Tool | Crop Genetics | Agricultural Sciences | Gwas, Genomic Prediction, Crop Genetics | Agricultural Sciences | Anvil: https://www.rcac.purdue.edu/software/gapit | Anvil: 3.3 | Bioinformatics | ||||
gatk | Aces, Anvil, Bridges-2, Expanse, Faster | GATK (Genome Analysis Toolkit) is a collection of command-line tools for analyzing high-throughput sequencing data with a primary focus on variant discovery. The tools can be used individually or chained together into complete workflows. Description Source: https://gatk.broadinstitute.org/hc/en-us/articles/360036194592-Getting-started-with-GATK4 |
The Genome Analysis Toolkit (GATK) is a widely used software package for variant discovery and genotyping analysis in high-throughput sequencing data. Developed by the Broad Institute, GATK provides a robust and comprehensive set of tools for processing raw sequencing data into accurate variant calls. | Core features of GATK include variant discovery, genotyping, recalibration of base quality scores, read alignment improvement, variant annotation, and various filtering and preprocessing steps. It supports a wide range of variant calling methodologies and has modules for germline and somatic variant detection. | https://gatk.broadinstitute.org/hc/en-us/articles/21904996835867--Tool-Documentation-Index | Tool | Sciences | Biology | Variant Calling, Genotyping, Sequencing Analysis | https://gatk.broadinstitute.org/hc/en-us | Biological Sciences | https://gatk.broadinstitute.org/hc/en-us/sections/360007226631-Tutorials | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gatk Bridges-2: https://www.psc.edu/resources/software/gatk Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.4.0.0-Java-17 Anvil: 3.8, 4.1.8.1 Bridges-2: 4.1.9.0 Expanse: Ybsfk6K Faster: 4.2.0.0-Java-1.8, 4.2.5.0-Java-11 |
Bioinformatics Tool | |
gatk4 | Anvil | GATK (Genome Analysis Toolkit) is a collection of command-line tools for analyzing high-throughput sequencing data with a primary focus on variant discoverye. | The Genome Analysis Toolkit (GATK) is a software package developed at the Broad Institute to analyze high-throughput sequencing data. The toolkit offers a wide variety of tools for variant discovery, genotyping, and other genomic analyses. | 1. Variant discovery and genotyping\r 2. Joint variant calling in cohorts\r 3. Quality control and variant filtration\r 4. Haplotype phasing and imputation\r 5. Structural variant discovery\r 6. Functional annotation of variants |
Genomic Analysis Tool | Genomics | Biological Sciences | Bioinformatics, Genomic Analysis, Variant Discovery, High-Throughput Sequencing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gatk4 | Anvil: 4.2.0, 4.2.5.0, 4.2.6.1, 4.3.0.0 | Data Analysis | ||||
gaussian | Bridges-2, Darwin, Expanse, Faster | Gaussian is a computational chemistry software for quantum mechanical simulations, widely used by researchers for studying molecular structures and reactions. It offers advanced capabilities in electronic structure prediction and various spectroscopic properties analysis. | Gaussian is a computational chemistry software suite used for electronic structure modeling. It is widely utilized in research and industry for predicting molecular properties and simulating chemical processes. | Key features of Gaussian include ab initio and density functional theory calculations, molecular dynamics simulations, electronic and vibrational spectroscopy, reaction mechanism analysis, and transition state optimization. It supports a wide range of methods and basis sets for accurate quantum chemical calculations. | https://gaussian.com/man/ | Simulation Software | Physical Chemistry | Chemical Sciences | Computational Chemistry, Quantum Chemistry, Molecular Modeling | https://gaussian.com/ | Natural Sciences | https://gaussian.com/faq/ https://www.youtube.com/GaussianInc |
Bridges-2: https://www.psc.edu/resources/software/gaussian Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Bridges-2: G16_Revc01 Expanse: 16.C.01-Cuda, 16.C.01 Faster: G16_B01, G16_C01 Stampede-3: 16Rc.01 |
Scientific Software | |
gaussian09 | Expanse | Gaussian09 is a software suite for quantum chemistry calculations, widely used for predicting molecular properties and behaviors based on quantum mechanics principles. | 1. Perform ab initio and DFT calculations for molecules and reactions.\r 2. Predict electronic and molecular structures, energies, and spectra.\r 3. Explore potential energy surfaces and reaction mechanisms.\r 4. Study molecular properties like dipole moments, polarizabilities, and vibrational frequencies. |
Computational Software | Physical Chemistry | Quantum Chemistry, Quantum Mechanics, Molecular Modeling | Chemical Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 09.D.01, 09.E.01 | Quantum Chemistry Software | ||||||
gawk | Faster, Kyric | GaussView aids in the creation of Gaussian input files, enables the user to run Gaussian calculations from a graphical interface without the need for using a command line instruction, and helps in the interpretation of Gaussian output. Description Source: https://gaussian.com/gaussview6/ |
Gawk is a powerful text processing utility that allows for pattern scanning and processing. It is based on the Awk programming language and is particularly useful for manipulating text files and generating reports. | 1. Pattern scanning and processing of text files\r 2. Automatic data restructuring and report generation\r 3. Advanced text manipulation capabilities\r 4. User-defined functions and variables\r 5. Conditional control structures for data processing |
https://gaussian.com/wp-content/uploads/dl/gv6.pdf | Text Processing Tool | Sciences | Chemistry | Text Processing, Data Manipulation, Pattern Scanning | https://gaussian.com/gaussview6/ | Computer & Information Sciences | https://gaussian.com/gv6main/ | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 5.0.1, 5.1.1 | Command-Line Utility | |
gc | Aces, Faster | The Boehm-Demers-Weiser conservative garbage collector can be used as a garbage collecting replacement for C malloc or C++ new. | GC is a compiler for the Go programming language. | GC provides garbage collection, concurrency support, memory safety, and a standard library. | Programming Language Compiler | Software Engineering, Systems, & Development | Computer Science | Compiler, Go, Garbage Collection, Concurrency | Computer & Information Sciences, Computer Science | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 8.2.0, 8.2.4 Faster: 7.6.12, 8.2.0, 8.2.4 |
Compiler | ||||
gcatools | Faster | gcatools is a set of tools designed to analyze and process genomic data generated from next-generation sequencing experiments. It offers a variety of functionalities for quality control, alignment, variant calling, and annotation of genomic sequences. | Quality Control Of Sequencing Data, Alignment Of Sequencing Reads To A Reference Genome, Identification Of Genetic Variants, Annotation Of Genomic Sequences | Tool | Genomics | Bioinformatics | Genomic Data Analysis, Next-Generation Sequencing, Bioinformatics | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.0 | Analysis Tool | |||||
gcc | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Kyric, Ookami, Stampede3 | GCC, the GNU Compiler Collection, is an open-source compiler system that supports various programming languages like C, C++, Objective-C, Fortran, Ada, and Go. It is widely used in software development for compiling source code into executable programs, providing robust performance and extensive compatibility across different platforms and operating systems. Description Source: https://gcc.gnu.org/ |
GNU Compiler Collection (GCC) is a free and open-source compiler system that supports various programming languages and platforms. It is widely used for compiling high-level programming languages into executable code for a variety of computer architectures. | 1. Supports multiple programming languages such as C, C++, Fortran, Ada, and Objective-C.\r 2. Optimizes code for better performance with various optimization levels.\r 3. Generates executable code for different target architectures.\r 4. Includes preprocessor for handling macro definitions and conditional compilation.\r 5. Provides extensive error and warning messages for code analysis.\r 6. Supports various platforms including Linux, Windows, macOS, and BSD. |
https://gcc.gnu.org/onlinedocs/gcc-13.2.0/gcc/ | Development Tools | Compiler, Software Development, Programming | https://gcc.gnu.org/ | Computer Science | https://gcc.gnu.org/wiki/GettingStarted https://gcc-newbies-guide.readthedocs.io/en/latest/ https://www.geeksforgeeks.org/gcc-command-in-linux-with-examples/ |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gcc Bridges-2: https://www.psc.edu/resources/software/gcc Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 8.3.0, 10.2.0, 10.3.0, 11.2.0, 11.3.0, 12.2.0, 12.3.0, 13.1.0, 13.2.0 Anvil: 8.4.1, 11.2.0-Openacc, 11.2.0 Bridges-2: 10.2.0, 13.2.1-P20240113 Delta: 11.4.0 Expanse: Xiuwkua Faster: 7.3.0-2.30, 8.3.0, 9.3.0, 10.2.0, 10.3.0, 11.2.0, 11.3.0, 12.1.0, 12.2.0, 12.3.0, 13.1.0, 13.2.0 Ookami: 9.4.0 Stampede-3: 13.2.0 |
Compiler | |||
gcc-native | Delta | gcc-native is a compiler system produced by the GNU Project supporting various programming languages, most notably C, C++, and Fortran. It is the default compiler for many Unix-like operating systems. | gcc-native provides compilers for various programming languages including C, C++, and Fortran. It supports optimization flags for performance tuning. The system includes a preprocessor, compiler, assembler, and linker. | Native Compiler | Software Development | Computer Science | Compiler, Gnu, Programming Language | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 10.3, 11.2 | Compiler | |||||
gcc-native-mixed | Delta | The gcc-native-mixed compiler is a version of the GNU Compiler Collection (GCC) that is specifically optimized for mixed-language programming, allowing developers to combine different programming languages within the same codebase. | Supports mixed-language programming, Optimized for combining multiple programming languages, High performance and efficiency, Comprehensive set of optimization flags, Advanced debugging capabilities | Development Tool | Compiler, Mixed-Language Programming, Optimization | Computer Science | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 10.3, 11.2 | Compiler | |||||||
gcc-nvptx | Expanse | The Nvidia PTX (Parallel Thread Execution) backend for GCC enables the generation of PTX code, which is a low-level parallel thread execution virtual machine and instruction set architecture used by Nvidia GPUs. It allows users to compile and optimize C and C++ code for Nvidia GPUs. | Generating Ptx Code For Nvidia Gpus, Compiling & Optimizing C & C++ Code For Gpu Execution | Programming Tool | Systems & Development | Computer Science | Compiler, Gpu Programming | Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 11.3.1 | Compiler | |||||
gcc-runtime | Delta | The GCC Runtime Library is a part of the GCC compiler collection that provides runtime support for programs compiled with GCC. It includes various runtime libraries and support files necessary for programs compiled with GCC to execute correctly. | 1. Includes runtime libraries needed for programs compiled with GCC. 2. Provides support files required for programs to run correctly. 3. Ensures compatibility and execution efficiency for programs compiled using GCC. | Runtime Library | Software Development | Software Engineering, Systems, & Development | Compiler, Runtime, Library | Engineering & Technology | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 8.5.0, 11.4.0 | Compiler | |||||
gcccore | Aces, Faster | The GNU Compiler Collection includes front ends for C, C++, Objective-C, Fortran, Ada, Go, and D, as well as libraries for these languages (libstdc++,...). GCC was originally written as the compiler for the GNU operating system. Description Source: https://gcc.gnu.org/ |
gcccore refers to the core components of the GNU Compiler Collection (GCC), which is a collection of compilers for several programming languages. These core components provide essential functionality for compiling code and generating executable programs. | Key features of gcccore include optimizing compilers for various programming languages such as C, C++, and Fortran, support for multiple architectures and operating systems, advanced optimization techniques, and extensive error-checking capabilities. | https://gcc.gnu.org/onlinedocs/gcc-13.2.0/gcc/ | Core Component | Compiler, Programming, Software Development | https://gcc.gnu.org/ | Computer & Information Sciences, Software Engineering, Systems, & Development | https://gcc.gnu.org/wiki/GettingStarted https://gcc-newbies-guide.readthedocs.io/en/latest/ https://www.geeksforgeeks.org/gcc-command-in-linux-with-examples/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 8.3.0, 10.2.0, 10.3.0, 11.2.0, 11.3.0, 12.2.0, 12.3.0, 13.1.0, 13.2.0 Faster: 7.3.0, 8.2.0, 8.3.0, 9.2.0, 9.3.0, 10.2.0, 10.3.0, 11.2.0, 11.3.0, 12.1.0, ... |
Compiler | |||
gcccuda | Aces, Faster | GNU Compiler Collection (GCC) based compiler toolchain, along with CUDA toolkit. | gcccuda is a wrapper around the GCC C compiler that enables CUDA programming directly in C without the need for NVCC. It allows developers to write CUDA code using familiar C syntax and compile it with the GCC compiler. | Enables Cuda Programming In C Using Gcc Compiler, No Need For Nvcc, Supports Cuda Features & Optimizations | https://gcc.gnu.org/onlinedocs/gcc-13.2.0/gcc/ | Development Tool | Parallel & Distributed Computing | Computer Science | Cuda Programming, C Compiler Wrapper, Parallel Computing | https://gcc.gnu.org/ | Computer & Information Sciences | https://gcc.gnu.org/wiki/GettingStarted https://gcc-newbies-guide.readthedocs.io/en/latest/ https://www.geeksforgeeks.org/gcc-command-in-linux-with-examples/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2020B Faster: 2019B, 2020A, 2020B |
Compiler | |
gconf | Aces, Faster | GConf is a system for storing application preferences. It is intended for user preferences; not configuration of something like Apache, or arbitrary data storage. | GConf is a configuration database system used by GNOME desktop environment and other GNOME software applications to store settings and preferences. It provides a centralized location for storing configuration data, allowing applications to access and update settings easily. | Centralized Configuration Database System, Used By Gnome Desktop Environment & Gnome Applications, Stores Settings & Preferences, Provides An Easy Way For Applications To Access & Update Configuration Data | Configuration Management System | Configuration Management, Settings, Preferences, Desktop Environment | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.2.6 Faster: 3.2.6 |
System Software | ||||||
gdal | Aces, Anvil, Darwin, Expanse, Faster | GDAL is a translator library for raster and vector geospatial data formats that is released under an MIT style Open Source License by the Open Source Geospatial Foundation. Description Source: https://gdal.org/ |
GDAL (Geospatial Data Abstraction Library) is a translator library for raster and vector geospatial data formats that is released under an X/MIT style Open Source license. It is a collection of geospatial data manipulation libraries that support raster and vector data formats, and includes protocols to access geospatial data sources. | Supports A Wide Range Of Raster & Vector Geospatial Data Formats, Ability To Translate Between Different Formats, Geospatial Data Manipulation Capabilities, Source, Coordinate System, & Reprojection Support, Can Be Used For Data Conversions, Processing, Analysis, & Visualization | https://gdal.org/user/index.html | Library | Geospatial Data, Raster Data, Vector Data, Data Formats, Geospatial Analysis | https://gdal.org/ | Earth & Environmental Sciences, Engineering & Technology | https://gdal.org/tutorials/index.html https://pcjericks.github.io/py-gdalogr-cookbook/ |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gdal Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.2.1, 3.3.0, 3.3.2, 3.5.0, 3.6.2, 3.7.1 Anvil: 2.4.4, 3.2.0 Expanse: Myvhqxy Faster: 3.0.4-Python-3.8.2, 3.2.1, 3.3.0, 3.3.2, 3.5.0, 3.6.2, 3.7.1 |
Geospatial Data Processing | |||
gdb | Aces, Anvil, Darwin, Expanse, Faster, Ookami | GDB, the GNU Project debugger, allows you to see what is going on `inside' another program while it executes -- or what another program was doing at the moment it crashed. Description Source: https://sourceware.org/gdb |
GDB, the GNU Project debugger, allows you to see what is going on 'inside' another program while it executes or what another program was doing at the moment it crashed. | 1. Source-level debugging: Supports multiple languages and allows debugging programs written in C, C++, Ada, Fortran, Go, and more. \r 2. Breakpoint management: Set breakpoints to pause the program execution at a specified point for inspection. \r 3. Watchpoints and catchpoints: Monitor and halt program execution when certain memory locations are accessed or when specific exception conditions occur. \r 4. Call stack and variables: View and manipulate the call stack, examine variables, and evaluate expressions. \r 5. Reverse debugging: Allows stepping backward through program execution to understand the causes of unexpected behavior. |
https://sourceware.org/gdb/current/onlinedocs/gdb.html/ | Debugger | Debugger, Programming, Software Development | https://www.sourceware.org/gdb/ | Computer & Information Sciences | https://sourceware.org/gdb/current/onlinedocs/gdb.html/Sample-Session.html#Sample-Session https://sourceware.org/gdb/wiki/ |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gdb Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 13.2 Anvil: 11.1 Expanse: Am633Ff, Vcxzknn, Xs4Oifw Faster: 13.2 Ookami: 11.1 |
Software Development Tools | |||
gdb4hpc | Delta | gdb4hpc is a plugin designed to enhance the GNU Debugger (GDB) for High Performance Computing (HPC) applications. It provides additional features to aid in debugging parallel and distributed applications typically used in HPC environments. | Some core features of gdb4hpc include advanced debugging capabilities for parallel and distributed applications, support for various HPC programming models such as MPI and OpenMP, improved performance analysis tools, integration with common HPC development environments, and enhanced visualization of parallel program execution. | Plugin | Software Engineering, Systems, & Development | Computer Science | Debugging, Hpc, Parallel Programming, Performance Analysis | Engineering & Technology | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 4.15.1 | Debugging Tools | |||||
gdbm | Faster, Kyric | GNU dbm (GDBM) is a library that provides an abstraction for a simple database manager. It allows for the creation and manipulation of key/value pairs in a persistent database, with support for fast lookup, retrieval, insertion, and deletion operations. | Supports Key/Value Pairs, Provides Persistent Storage, Allows Fast Lookup & Retrieval Operations, Enables Efficient Insertion & Deletion Of Data, Offers Api For Database Management | https://www.gnu.org.ua/software/gdbm/manual/index.html | Library | Database Management, Key-Value Store, Persistent Storage, Api | https://www.gnu.org.ua/software/gdbm/ | Computer & Information Sciences | https://www.gnu.org.ua/software/gdbm/manual/Intro.html | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.18.1 | Data Management & Storage | ||||
gdk-pixbuf | Aces, Faster | The Gdk Pixbuf package is a toolkit for image loading and pixel buffer manipulation. It is used by GTK+ 2 and GTK+ 3 to load and manipulate images. In the past it was distributed as part of GTK+ 2 but it was split off into a separate package in preparation for the change to GTK+ 3. Description Source: https://www.linuxfromscratch.org/blfs/view/11.2/x/gdk-pixbuf.html |
The GdkPixbuf library provides a way to load images into a program and manipulate those images. It is used by GTK and GNOME applications to handle images. GdkPixbuf supports loading, saving, scaling, compositing, and transforming images, allowing various graphical operations to be performed on the images. | 1. Image loading and saving capabilities.\r 2. Image scaling and transformations.\r 3. Image compositing.\r 4. Support for various image formats. |
https://docs.gtk.org/gdk-pixbuf/ | Image Processing | Image Processing, Graphics, Library | https://gitlab.gnome.org/GNOME/gdk-pixbuf | Computer & Information Sciences | https://docs.gtk.org/gdk-pixbuf/class.Pixbuf.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.42.6, 2.42.8, 2.42.10 Faster: 2.38.2, 2.40.0, 2.42.0, 2.42.6, 2.42.8, 2.42.10 |
Library | |||
gdrcopy | Aces, Delta, Faster | GDRCopy is a low-latency GPU memory copy library based on GPUDirect RDMA technology that allows the CPU to directly map and access GPU memory. GDRCopy also provides optimized copy APIs and is widely used in high-performance communication runtimes like UCX, OpenMPI, MVAPICH, and NVSHMEM. Description Source: https://developer.nvidia.com/gdrcopy |
gdrcopy is a CUDA accelerated GPU memory copy library for NVIDIA GPUs. It provides efficient memory copy operations between host and device memory with the use of asynchronous memory copies and supports different data types for optimal performance. | 1. CUDA accelerated GPU memory copy operations\r 2. Support for asynchronous memory copies\r 3. Efficient data transfer between host and device memory\r 4. Optimization for different data types\r 5. Compatible with NVIDIA GPUs |
https://github.com/NVIDIA/gdrcopy | Memory Management | Parallel Computing | Computer Science | Gpu Memory Copy, Cuda Acceleration, Asynchronous Memory Copies | https://developer.nvidia.com/gdrcopy | Computer & Information Sciences | https://github.com/NVIDIA/gdrcopy?tab=readme-ov-file#tests | Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.1-Cuda-11.1.1, 2.2, 2.3, 2.3.1, 2.4 Delta: 2.3 Faster: 2.1-Cuda-11.0.2, 2.1-Cuda-11.1.1, 2.2, 2.3, 2.3.1 |
Library | |
geant4 | Aces | Geant4 is a toolkit for the simulation of the passage of particles through matter. Its areas of application include high energy, nuclear and accelerator physics, as well as studies in medical and space science. | GEANT4 is a toolkit for the simulation of the passage of particles through matter. It is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics, and radiation protection. | Monte Carlo Simulation Of Particle Transport Through Matter, Modular Design With A Wide Range Of Physics Processes & Geometries, User-Friendly Interfaces & Visualization Tools, Open-Source & Actively Maintained By A Large International Collaboration | Toolkit | High Energy Physics | Particle Physics | Software, Physics, Simulation, Particle Transport | Physical Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 11.1.2 | Simulation Software | ||||
geant4-data | Aces | Datasets for Geant4. | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 11.1 | ||||||||||||
gemma | Anvil | Gemma is a software toolkit for fast application of linear mixed models (LMMs) and related models to genome-wide association studies (GWAS) and other large-scale data sets. | Gemma is a software package for genome-wide association analysis in a mixed model framework. It can efficiently handle large-scale genotype data for a wide range of genetic analysis. | 1. Genome-wide association analysis\r 2. Mixed model framework\r 3. Efficient handling of large-scale genotype data\r 4. Wide range of genetic analysis capabilities |
Genetic Analysis | Genome-Wide Association Analysis, Genetic Analysis, Mixed Model Framework | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gemma | Anvil: 0.98.3 | Bioinformatics | ||||||
gemoma | Anvil | Gene Model Mapper (GeMoMa) is a homology-based gene prediction program. | GEMoma (Gene Mapper for RNA-Seq Data) is a tool designed for rapid and accurate mapping of RNA-Seq data to a reference genome. | GEMoma utilizes a fast and memory-efficient seed-and-extend algorithm to map RNA-Seq reads effectively. It supports various parameters customization for mapping precision. The tool also provides visualization options for mapped reads and gene expression levels. | Genome Mapping Tool | Computational Biology | Bioinformatics | RNA-Seq, Genome Mapping, Gene Expression, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gemoma | Anvil: 1.7.1 | Bioinformatics Tool | ||||
genemark | Anvil | GeneMark-ES/ET/EP is package including GeneMark-ES, GeneMark-ET and GeneMark-EP+ algorithms. | GeneMark is a gene prediction software for prokaryotic and eukaryotic genomes. It uses state-of-the-art algorithms to accurately identify protein-coding genes. | 1. Prediction of protein-coding genes in prokaryotic and eukaryotic genomes.\r 2. Utilizes advanced algorithms for accurate gene prediction.\r 3. Provides annotations for predicted genes. |
Algorithm | Genomics | Bioinformatics | Gene Prediction, Prokaryotic Genomes, Eukaryotic Genomes | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/genemark | Anvil: 4.68, 4.69 | Gene Prediction | ||||
genemark-es | Bridges-2 | Novel eukaryotic genomes can be analyzed by the self-training GeneMark-ES. Description Source: http://exon.gatech.edu/GeneMark/ |
GeneMark-ES (Eukaryotic) is a eukaryotic gene prediction software that accurately predicts the location and structure of protein-coding genes in eukaryotic genomes. It is based on an unsupervised ab initio approach using hidden Markov model algorithms. | Accurate Prediction Of Protein-Coding Genes In Eukaryotic Genomes, Unsupervised Ab Initio Gene Prediction Approach, Hidden Markov Model Algorithms | https://github.com/gatech-genemark/GeneMark-E-Docs/tree/main/docs | Gene Prediction Software | Genetics | Biological Sciences | Gene Prediction, Bioinformatics, Eukaryotic Genomes, Hidden Markov Model | http://exon.gatech.edu/GeneMark/ | Biological Sciences | https://github.com/gatech-genemark/GeneMark-E-Docs/blob/main/docs/usage/general.md https://github.com/gatech-genemark/GeneMark-E-Docs/tree/main/docs/examples |
Bridges-2: https://www.psc.edu/resources/software/genemark-es | Bridges-2: 4.65 | Bioinformatics Tool | |
genemarks-2 | Anvil | GeneMarkS-2 combines GeneMark.hmm (prokaryotic) and GeneMark (prokaryotic) with a self-training procedure that determines parameters of the models of both GeneMark.hmm and GeneMark. | GeneMarkS-2 is a gene prediction software that utilizes a self-training algorithm to predict genes in prokaryotic genomes. It identifies protein-coding genes, ribosomal RNA genes, and tRNA genes based on hidden Markov models. | Gene Prediction In Prokaryotic Genomes, Self-Training Algorithm, Identification Of Protein-Coding Genes, Ribosomal RNA Genes, & Trna Genes, Utilizes Hidden Markov Models | Prokaryotic Gene Prediction | Gene Annotation | Genomics | Gene Prediction, Prokaryotic Genomes, Hidden Markov Models | Anvil: https://www.rcac.purdue.edu/software/genemarks-2 | Anvil: 1.14_1.25 | Genome Annotation | |||||
generativemodels | Aces | Project MONAI is a set of open-source, freely available collaborative frameworks built for accelerating research and clinical collaboration in Medical Imaging. The goal is to accelerate the pace of innovation and clinical translation by building a robust software framework that benefits nearly every level of medical imaging, deep learning research, and deployment. | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.2.1-Cuda-11.7.0 | ||||||||||||
genmap | Anvil | GenMap: Ultra-fast Computation of Genome Mappability. | GenMap is a software tool designed for genetic mapping studies, particularly in the context of linkage analysis. It is used to map genetic loci to specific regions of chromosomes by analyzing the inheritance patterns of genetic markers within families. | 1. Genetic mapping for linkage analysis\r 2. Analysis of inheritance patterns of genetic markers\r 3. Mapping genetic loci to chromosomal regions\r 4. Family-based genetic studies support\r 5. Visualization of linkage results |
Genetic Mapping Software | Genetic Mapping, Linkage Analysis, Genetic Loci Mapping, Family-Based Studies | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/genmap | Anvil: 1.3.0 | Bioinformatics Tool | ||||||
genomedata | Anvil | Genomedata is a format for efficient storage of multiple tracks of numeric data anchored to a genome. | genomedata is a Python package that provides efficient and convenient access to genome data and annotations. It allows users to work with genomic data in a structured and standardized manner, enabling easy manipulation, analysis, and visualization of genomics data. | Efficient Access To Genome Data & Annotations, Structured & Standardized Handling Of Genomic Data, Data Manipulation, Analysis, & Visualization Capabilities, Integration With Popular Python Libraries For Genomics | Data Processing | Genomics | Biological Sciences | Genomics, Python Package, Data Analysis, Data Visualization | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/genomedata | Anvil: 1.5.0 | Library | ||||
genomepy | Anvil | Genomepy is designed to provide a simple and straightforward way to download and use genomic data. | Genomepy is a Python package for downloading reference genomes and associated annotation files from various sources. It simplifies the process of obtaining genomic data required for bioinformatics analysis. | Automatic Download Of Reference Genomes, Support For Multiple Genome Sources Such As Ncbi, Ensembl, Ucsc, Integration With Popular Bioinformatics Tools, Ability To Update & Manage Local Genome Databases | Python Library | Bioinformatics | Genomics | Genomics, Bioinformatics, Python, Reference Genomes, Sequence Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/genomepy | Anvil: 0.12.0, 0.14.0 | Data Management | ||||
genomescope2 | Anvil | Genomescope2: Reference-free profiling of polyploid genomes | GenomeScope 2 is a software tool for estimating genome characteristics such as heterozygosity, repeat content, and genome size from high-throughput sequencing reads using a k-mer based approach. | - Heterozygosity estimation\r - Repeat content estimation\r - Genome size estimation\r - K-mer analysis |
Bioinformatics Tool | Genome Characterization | Genomics | Genome Analysis, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/genomescope2 | Anvil: 2.0 | Genome Analysis Tool | ||||
genomicconsensus | Anvil | Genomicconsensus is the current PacBio consensus and variant calling suite. | GenomicConsensus is a tool for refining consensus sequence calls produced by bioinformatics applications, primarily focusing on long and error-prone Third Generation Sequencing (TGS) platforms such as PacBio Single Molecule, Real-Time (SMRT) sequencing. | Refining Consensus Sequence Calls, Optimizing Error Correction, Focused On Long & Error-Prone Tgs Platforms, Integration With Bioinformatics Workflows | Bioinformatics Tool | Sequence Analysis | Genomics | Bioinformatics, Genomics, Sequence Analysis, Error Correction | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/genomicconsensus | Anvil: 2.3.3 | Genome Analysis | ||||
genrich | Anvil | Genrich is a peak-caller for genomic enrichment assays (e.g. ChIP-seq, ATAC-seq). It analyzes alignment files generated following the assay and produces a file detailing peaks of significant enrichment. | Genrich is a tool designed for analyzing ChIP-seq data, specifically focused on identifying significant regions of enrichment in datasets. | Identification Of Enriched Regions In Chip-Seq Data, Statistical Analysis For Significance Assessment, Integration With Genomic Coordinates & Sequence Data, Visualization Of Results For Interpretation | Tool | Chromatin Biology | Genomics & Bioinformatics | Chip-Seq Analysis, Enriched Regions Identification, Bioinformatics Tool | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/genrich | Anvil: 0.6.1 | Bioinformatics | ||||
gent | Bridges-2 | GeNT is a FORTRAN program that computes the cross entropy for groups of sequences that have been assigned to groups on the basis of biochemical,physiological, or other biological property. The sequence assignments are cross-validated, again by the cross entropy measure, to check for problems with the alignment or group assignment. Sequences that were initially identified as “unclassified” are compared to all of the groups using position specific log-odds scores as described by Henikoff and Henikoff. Positions in the aligned sequences that are important for determining group membership are identified by having a high entropy for the entire alignment and a high entropy for one or more specific groups. Description Source: https://www.psc.edu/resources/software/gent/ |
Gent is a graph-based DNA comparison tool that enables the identification of structural variants, inversions, deletions, insertions, duplications, and translocations in the human genome. | 1. Detection of structural variants in DNA sequences.\r 2. Graph-based approach for accurate variant identification.\r 3. Ability to detect various types of variations such as inversions, deletions, insertions, duplications, and translocations.\r 4. Analysis of structural variations in the human genome. |
https://www.psc.edu/resources/software/gent/ | Bioinformatics Tool | Genomics | Bioinformatics | DNA Comparison, Structural Variants, Genomics | https://www.psc.edu/resources/software/gent/ | Biological Sciences | Bridges-2: https://www.psc.edu/resources/software/gent | Bridges-2: 1.0.0 | Computational Tool | ||
geocube | Faster | Geocube is a Python library for generating interactive 3D visualizations of geospatial data. It is designed to facilitate the creation of immersive and dynamic representations of geospatial information for research, analysis, and presentation purposes. | 1. Supports visualization of geospatial data in a 3D environment.\r 2. Allows for interactive exploration of spatial datasets.\r 3. Enables customization of visual elements such as colors, textures, and annotations.\r 4. Provides tools for adding interactive controls and user interactions.\r 5. Compatible with popular geospatial data formats and libraries. |
Python Library | Geophysics & Geochemistry | Earth & Environmental Sciences | Geospatial Data, 3D Visualization, Python Library | Physical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.0.14-Python-3.8.2 | Visualization Tool | |||||
geomview | Darwin | Geomview is an interactive 3D viewing program for Unix. It lets you view and manipulate 3D objects: you use a mouse to rotate, translate, zoom in and out, etc. It reads and writes files in any of the formats supported by your 3D graphics library. | Interactive 3D Viewing Of Objects, Rotation, Translation, Zooming Functionality, Support For Multiple File Formats, Customizable Display Options, Compatibility With Unix Systems | 3D Viewing | 3D Visualization, Interactive Viewing, Unix Software | Computer & Information Sciences | Visualization Tool | |||||||||
geopandas | Aces, Faster | GeoPandas is a project to add support for geographic data to pandas objects. It currently implements GeoSeries and GeoDataFrame types which are subclasses of pandas.Series and pandas.DataFrame respectively. GeoPandas objects can act on shapely geometry objects and perform geometric operations. | Geopandas is an open-source python library for working with geospatial data, enabling users to easily manipulate and analyze geospatial datasets. | Reading & Writing Spatial Data Formats, Spatial Operations & Manipulations, Attribute Joins Between Geospatial Datasets, Handling Of Coordinate Reference Systems (Crs), Visualization Of Geospatial Data | Data Analysis | Geospatial Data, Python Library, Geospatial Analysis | Earth & Environmental Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.12.2 Faster: 0.8.1-Python-3.8.2 |
Python Library | ||||||
geos | Aces, Anvil, Darwin, Expanse, Faster, Ookami | GEOS is a C/C++ library for computational geometry with a focus on algorithms used in geographic information systems (GIS) software. It implements the OGC Simple Features geometry model and provides all the spatial functions in that standard as well as many others. Description Source: https://libgeos.org/ |
Geos is an open-source geometry engine that provides C++ software libraries and tools for processing spatial data. It is a key component of the PostGIS spatial database extender and is used in various GIS software applications. | Geos offers robust support for geometric operations such as buffering, intersection, union, and difference. It provides functionalities for handling various geometric objects like points, lines, polygons, and collections. Geos also includes algorithms for validating geometries and simplifying complex geometric structures. | https://libgeos.org/doxygen/ | Geospatial Software | Geographic Information Systems | Other Computer & Information Sciences | Geometry Engine, Spatial Data Processing, Gis, Open-Source | https://libgeos.org/ | Computer & Information Sciences | https://libgeos.org/usage/c_api/ https://libgeos.org/usage/cpp_api/ https://github.com/libgeos/geos/tree/main/examples |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/geos Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 3.9.1, 3.10.3, 3.11.1, 3.12.0 Anvil: 3.8.1, 3.9.1 Expanse: Ad5Oco3 Faster: 3.8.1-Python-3.8.2, 3.9.1, 3.10.3, 3.11.1, 3.12.0 Ookami: Gcc12.1/3.11.0 |
Library | |
getdist | Faster | GetDist is a Python package for analyzing Monte Carlo Markov Chains (MCMC) samples, primarily used in cosmological parameter estimation. It provides tools for plotting and analyzing MCMC samples, computing confidence limits, and generating parameter constraints and posterior plots. | Analysis Of Mcmc Samples, Parameter Estimation In Cosmology, Generation Of Parameter Constraints & Posterior Plots, Computation Of Confidence Limits | Python Library | Cosmology | Astronomy & Planetary Sciences | Mcmc Analysis, Parameter Estimation, Posterior Plots, Cosmology | Physical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.4 | Data Analysis | |||||
gethost | Ookami | gethost is a command-line utility that retrieves the IP address and hostname of a specified domain or URL. It can be used to quickly obtain network information during troubleshooting or system administration tasks. | 1. Retrieve the IP address and hostname of a domain or URL.\r 2. Simple and straightforward command-line interface.\r 3. Useful for network troubleshooting and system administration. |
Networking Tool | Networking, Command-Line, System Administration | Computer & Information Sciences | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 1.0 | Command-Line Utility | |||||||
getorganelle | Anvil | Getorganelle is a fast and versatile toolkit for accurate de novo assembly of organelle genomes. | GetOrganelle is a software package that enables de novo assembly, homology search, and gene annotation for organelle genomes. | De Novo Assembly Of Organelle Genomes, Homology Search, Gene Annotation | Analysis Tool | Organelle Genomics | Genomics | Bioinformatics, Genomics, Molecular Biology, Computational Biology | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/getorganelle | Anvil: 1.7.7.0 | Bioinformatics Tool | ||||
gettext | Aces, Bridges-2, Faster, Kyric | Gettext is a software framework used for internationalization and localization of software applications, allowing them to be translated into multiple languages. It provides tools for developers to extract strings from their code, create and manage translation files, and compile these files into formats that can be used by the application to display the translated text, thereby making the software accessible to a global audience. | GNU gettext is a package providing a framework for internationalization and localization of software. It includes tools for extracting translatable strings from source code, for generating message catalogs (pot files), and for translating the strings into different languages. | Internationalization (I18N), Localization (L10N), Extracting Translatable Strings, Generating Message Catalogs, Translating Strings | https://www.gnu.org/software/gettext/manual/index.html | Localization Tool | Internationalization, Localization, Software Development | https://www.gnu.org/software/gettext/ | Computer & Information Sciences | https://www.labri.fr/perso/fleury/posts/programming/a-quick-gettext-tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ Bridges-2: https://www.psc.edu/resources/software/gettext Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.21, 0.21.1, 0.22 Bridges-2: 0.22.5-Gcc13.2.1-P20240113 Faster: 0.19.8.1, 0.20.1, 0.21, 0.21.1, 0.22 |
Compilers | |||
gfaffix | Anvil | GFAffix identifies walk-preserving shared affixes in variation graphs and collapses them into a non-redundant graph structure. | Gfaffix is a computational software package designed for analyzing genomic data, specifically focused on functional annotation and analysis of DNA sequences. | Functional Annotation Of DNA Sequences, Genomic Data Analysis, Identification Of Regulatory Elements, Visualization Tools For Genomic Data | Computational Tool | Functional Genomics | Genomics | Computational Software, Genomic Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gfaffix | Anvil: 0.1.4 | Bioinformatics | ||||
gfastats | Anvil | gfastats is a single fast and exhaustive tool for summary statistics and simultaneous *fa* (fasta, fastq, gfa [.gz]) genome assembly file manipulation. | gfastats is a Python library for statistical functions and data analysis, providing a wide range of functions for descriptive statistics, hypothesis testing, and regression analysis. | Descriptive Statistics, Hypothesis Testing, Regression Analysis, Data Analysis | Statistical Analysis Tool | Python Library, Statistical Functions, Data Analysis | Other Mathematics | Anvil: https://www.rcac.purdue.edu/software/gfastats | Anvil: 1.2.3, 1.3.6 | Python Library | ||||||
gfatools | Anvil | gfatools is a set of tools for manipulating sequence graphs in the GFA or the rGFA format. It has implemented parsing, subgraph and conversion to FASTA/BED. | gfatools is a suite of tools for working with genomic sequence graphs and genome variation graphs. It provides functionalities for manipulating genomic graphs, performing sequence alignment on graphs, and analyzing variations within graphs. | 1. Manipulation of genomic sequence graphs\r 2. Sequence alignment on graphs\r 3. Analysis of genome variations within graphs |
Tool | Genetics | Biological Sciences | Genomics, Genome Variation Graphs, Sequence Alignment, Variation Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gfatools | Anvil: 0.5 | Bioinformatics | ||||
gfbf | Aces, Faster | GNU Compiler Collection (GCC) based compiler toolchain, including FlexiBLAS (BLAS and LAPACK support) and (serial) FFTW. | Gfbf is a compiler for Boolean functions, implemented as an SMT/SAT translation tool. It takes a Boolean function expressed as an algebraic normal form (ANF) as input and produces output in various formats including Conjunctive Normal Form (CNF), Decision Diagrams, and Truth Tables. The tool is designed to efficiently manipulate and analyze Boolean functions for various applications in logic synthesis, verification, and optimization. | Boolean Function Compilation, Anf To Cnf Conversion, Smt/Sat Translation, Decision Diagram Generation, Truth Table Export | Compilation Tool | Artificial Intelligence & Intelligent Systems | Computer Science | Compiler, Boolean Functions, Logic Synthesis, Verification, Optimization | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2022A, 2022B, 2023A, 2023B, 2023.09 Faster: 2022A, 2022B, 2023A |
Compiler | ||||
gffcompare | Anvil | Gffcompare is used to compare, merge, annotate and estimate accuracy of one or more GFF files. | gffcompare is a tool for evaluating the accuracy of RNA-Seq transcript assemblers and for annotating genomic features. | Compare, Evaluate, & Classify Transcript Models, Determine Relationships Between Reference Transcripts & Assembled Transcripts, Produce Various Statistics & Visualization Plots For Comparison | Computational Tool | RNA-Seq, Transcript Assembly, Genome Annotation | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gffcompare | Anvil: 0.11.2 | Bioinformatics | ||||||
gffread | Anvil | Gffread is used to validate, filter, convert and perform various other operations on GFF files. | gffread is a tool for converting GFF3 files to FASTA format. It extracts sequences based on feature type or ID, translates CDS features to proteins, and more. | 1. Converts GFF3 files to FASTA format. 2. Extracts sequences based on feature type or ID. 3. Translates CDS features to proteins. 4. Supports filtering by attributes or locations. | Tool | Gff3, Fasta, Sequence Processing | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gffread | Anvil: 0.12.7 | Bioinformatics | ||||||
gffutils | Anvil | gffutils is a Python package for working with and manipulating the GFF and GTF format files typically used for genomic annotations. | gffutils is a Python package for working with and manipulating GFF (General Feature Format) files, a tab-delimited file format that stores genomic features. It provides tools for parsing, querying, and analyzing GFF files. | Parsing & Reading Gff Files, Querying Genomic Features, Filtering & Manipulating Gff Data, Converting Gff Files To Different Formats, Integration With Python For Further Analysis | Bioinformatics Tool | Genomics | Genomic Data, Bioinformatics, Python Library, File Parsing, Data Manipulation | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gffutils | Anvil: 0.11.1 | Data Processing & Analysis | |||||
gh | Delta, Expanse | https://cli.github.com/manual/gh | https://docs.github.com/en/github-cli | https://docs.github.com/en/github-cli/github-cli/quickstart | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Delta: 2.32.1 Expanse: Eytgnon, Mkz3Uxl |
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ghostscript | Aces, Anvil, Faster | Ghostscript is an interpreter for the PostScript® language and PDF files. It is available under either the GNU GPL Affero license or licensed for commercial use from Artifex Software, Inc. Ghostscript consists of a PostScript interpreter layer and a graphics library. Description Source: https://ghostscript.com/ |
Ghostscript is a versatile software suite for viewing, converting, and printing PostScript and PDF files. It is widely used for rasterizing files for high-quality printing and viewing on a variety of devices. | 1. Interpret and render PostScript and PDF files\r 2. Convert files between different formats\r 3. Manipulate graphics and images\r 4. Display and print documents\r 5. Scriptable interface for automation |
https://ghostscript.readthedocs.io/en/latest/ | Software Development | Document-Processing, File-Conversion, Print-Management | https://ghostscript.com/ | Computer & Information Sciences, Engineering & Technology | https://ghostscript.readthedocs.io/en/latest/Use.html https://ghostscript.readthedocs.io/en/latest/Source.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/ghostscript Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 9.54.0, 9.56.1, 10.0.0, 10.01.2 Anvil: 9.56.1 Faster: 9.52, 9.53.3, 9.54.0, 9.56.1, 10.0.0, 10.01.2 |
Utility | |||
giflib | Aces, Faster | Giflib is a software package designed for reading and writing GIF (Graphics Interchange Format) images. It provides a set of utilities for processing GIFs, including conversion to and from various formats, making it a valuable tool for developers working with GIF animations and image processing in applications or web services. | Giflib is a library for reading and writing GIF images. It is a widely used library for handling Graphics Interchange Format (GIF) images in various software applications and programming languages. | Reading & Writing Gif Images, Support For Various Gif Image Manipulation Functions, High Performance & Efficient Gif Image Processing, Cross-Platform Compatibility | https://giflib.sourceforge.net/gif_lib.html | Package | Library, Image Processing, Gif Images | https://giflib.sourceforge.net/ | https://giflib.sourceforge.net/whatsinagif/index.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.2.1 Faster: 5.2.1 |
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gimmemotifs | Anvil | GimmeMotifs is a suite of motif tools, including a motif prediction pipeline for ChIP-seq experiments. | Gimmemotifs is a software package for de novo motif discovery, motif comparison and scanning for known motifs in DNA sequences. It provides a unified framework for running multiple motif discovery tools and merging the results to improve motif predictions. | 1. De novo motif discovery\r 2. Motif comparison\r 3. Scanning for known motifs in DNA sequences\r 4. Unified framework for running multiple motif discovery tools\r 5. Merging results to improve motif predictions |
Bioinformatics | Genetics | Biological Sciences | Motif Discovery, DNA Sequences, Motif Comparison, Motif Scanning | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gimmemotifs | Anvil: 0.17.1 | Computational Biology | ||||
git | Aces, Darwin, Delta, Expanse, Faster, Kyric, Ookami | Git is a distributed version control system, widely used for tracking changes in source code during software development. It allows multiple developers to work collaboratively on a project, providing tools for managing versions, resolving conflicts, and maintaining a history of changes made to the codebase. | Git is a distributed version control system designed to handle everything from small to very large projects with speed and efficiency. It is an open-source tool that is widely used for source code management in software development. | Distributed Version Control System, Branching & Merging, Security & Encryption, Staging Areas, Collaboration Tools | https://git-scm.com/docs | Development Tools | Version Control, Software Development, Source Code Management | https://git-scm.com/ | Computer & Information Sciences, Software Engineering, Systems, & Development | https://git-scm.com/docs/gittutorial https://www.youtube.com/watch?v=HVsySz-h9r4 https://www.atlassian.com/git/tutorials |
Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 2.28.0-Nodocs, 2.32.0-Nodocs, 2.33.1-Nodocs, 2.36.0-Nodocs, 2.38.1-Nodocs, 2.41.0-Nodocs, 2.42.0 Delta: 2.39.3 Expanse: Darghpu, Ldetm5Y Faster: 2.23.0-Nodocs, 2.28.0-Nodocs, 2.32.0-Nodocs, 2.33.1-Nodocs, 2.36.0-Nodocs, 2.38.1-Nodocs, 2.41.0-Nodocs Ookami: 2.38.1 |
Version Control System | |||
git-lfs | Aces, Darwin, Delta, Expanse, Faster | Git Large File Storage (LFS) replaces large files such as audio samples, videos, datasets, and graphics with text pointers inside Git, while storing the file contents on a remote server like GitHub.com or GitHub Enterprise. | Git Large File Storage (LFS) is a Git extension that reduces the impact of large files in your repository by replacing them with text pointers while storing the actual file content on a remote server. It seamlessly integrates with Git and provides efficient handling of large files, making it easier to work with version-controlled repositories containing large assets. | Efficient Handling Of Large Files, Reduced Impact Of Large Files In Repositories, Text Pointers For Large Files While Storing In Remote Server, Seamless Integration With Git | https://github.com/git-lfs/git-lfs/tree/main/docs | Development Tool | Version Control, File Storage, Git Extension | https://git-lfs.com/ | Engineering & Technology | https://github.com/git-lfs/git-lfs/wiki/Tutorial https://github.com/git-lfs/git-lfs/wiki |
Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.2.0, 3.3.0 Delta: 3.3.0 Expanse: Kmruniy, 32Gm6Hi Faster: 3.2.0, 3.4.0 |
Version Control System | |||
gitpython | Faster | GitPython is a python library used to interact with Git repositories. It provides a high-level API that allows for interfacing with Git commands and repositories directly from Python scripts. | 1. Ability to interface with Git repositories within Python scripts\r 2. Supports common Git operations like cloning, committing, pushing, and pulling\r 3. Provides access to Git's objects (commits, trees, blobs) and references (branches, tags)\r 4. Offers options for working with submodules and managing repository information |
Development | Version Control, Source Code Management, Python Library | Computer Science | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.1.27 | Library | |||||||
gklib | Aces, Stampede3 | A library of various helper routines and frameworks used by Karypis Lab software such as METIS. | gklib is a C++ library for geometric kernels that provides efficient and accurate geometric algorithms for computational geometry and related fields. | The core features of gklib include robust and reliable geometric algorithms for tasks such as intersection detection, proximity queries, convex hull computation, point location, and triangulation. | Computational Software | Computational Geometry | Applied Mathematics | Geometric Kernels, Computational Geometry, Algorithms | Mathematics | Aces: https://hprc.tamu.edu/software/aces/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 5.1.1, 20231211, 20240119, 20240321, 20240329 Stampede-3: Git20240111 |
Library | ||||
gl2ps | Aces, Faster | GL2PS is a C library providing high quality vector output for any OpenGL application. The main difference between GL2PS and other similar libraries is the use of sorting algorithms capable of handling intersecting and stretched polygons, as well as non manifold objects. GL2PS provides advanced smooth shading and text rendering, culling of invisible primitives, mixed vector/bitmap output, and much more... Description Source: https://www.geuz.org/gl2ps/ |
GL2PS is an OpenGL to PostScript printing library that converts any OpenGL action into a vector PostScript image. It provides capabilities for saving OpenGL-generated 2D and 3D graphics as encapsulated PostScript files. GL2PS is written in C++ and can be easily integrated into existing OpenGL code. | 1. Conversion of OpenGL graphics to PostScript format\r 2. Support for 2D and 3D graphics\r 3. Integration with existing OpenGL applications\r 4. Vector-based output for high-quality printing\r 5. Cross-platform compatibility |
https://www.geuz.org/gl2ps/#tth_sEc2 | Library | Opengl, Postscript, Printing, Graphics, Vector Graphics | https://www.geuz.org/gl2ps/ | https://www.geuz.org/gl2ps/#tth_sEc3 https://www.geuz.org/gl2ps/#tth_sEc4 https://github.com/Open-Cascade-SAS/gl2ps/blob/occt-emf/gl2psTest.c |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.4.2 Faster: 1.4.2 |
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glew | Aces, Faster | The OpenGL Extension Wrangler Library (GLEW) is a cross-platform open-source C/C++ extension loading library. GLEW provides efficient run-time mechanisms for determining which OpenGL extensions are supported on the target platform. | The OpenGL Extension Wrangler Library (GLEW) is a cross-platform open-source C/C++ extension loading library. It assists in accessing OpenGL extensions and functions dynamically, providing a simple and lightweight solution for managing OpenGL extensions. | 1. Cross-platform support\r 2. Dynamic loading of OpenGL extensions\r 3. Lightweight and easy to use\r 4. Simplifies managing OpenGL extensions\r 5. Open-source with a permissive license |
Tool | Opengl, Extension Loader, C/C++ Library | Computer Science | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.2.0-Egl Faster: 2.2.0-Egl, 2.2.0-Osmesa |
Library | ||||||
glfw | Aces, Faster | GLFW is an Open Source, multi-platform library for OpenGL, OpenGL ES and Vulkan development on the desktop. It provides a simple API for creating windows, contexts and surfaces, receiving input and events. Description Source: https://www.glfw.org/ |
GLFW is an open-source, multi-platform library for creating windows with OpenGL contexts and managing input. It provides a simple API for creating and managing windows, contexts, and surfaces, receiving input events. GLFW is written in C and provides native support for Windows, macOS, and Linux, as well as experimental support for mobile platforms. | Cross-Platform Window Creation & Management, Opengl Context Creation, Input Handling (Keyboard, Mouse, Gamepad), Event Callbacks, Monitor Handling For Fullscreen Windows, File & Drag-&-Drop Support | https://www.glfw.org/docs/latest/ | Development Tool | Graphics, Opengl, Cross-Platform, Window Management, Input Handling | https://www.glfw.org/ | Computer & Information Sciences | https://www.glfw.org/docs/latest/quick.html https://www.glfw.org/docs/latest/intro_guide.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.3.8 Faster: 3.3.4, 3.3.8 |
Library | |||
glib | Aces, Faster | GLib is a general-purpose, portable utility library, which provides many useful data types, macros, type conversions, string utilities, file utilities, a mainloop abstraction, and so on. It is one of the base libraries of GTK+. Description Source: https://docs.gtk.org/glib/ |
GLib is a general-purpose utility library for the C programming language. It provides data structure handling for lists, trees, hashes, memory allocation, and other commonly needed functionality. | Data Structure Handling For Lists, Trees, & Hashes, Memory Management & Allocation, Thread Support, Internationalization Support, Dynamic Loading Of Modules, Utilities For Strings & File Manipulation | https://docs.gtk.org/glib/ | Utility | Utility Library, C Programming, Data Structures, Memory Management, Thread Support | https://gitlab.gnome.org/GNOME/glib/ | Computer & Information Sciences | https://docs.gtk.org/glib/programming.html https://docs.gtk.org/glib/types.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.66.1, 2.68.2, 2.69.1, 2.72.1, 2.75.0, 2.77.1 Faster: 2.62.0, 2.64.1, 2.66.1, 2.68.2, 2.69.1, 2.72.1, 2.75.0, 2.77.1 |
Library | |||
glib-networking | Aces, Faster | Network extensions for GLib | Glib-networking is a set of network-related GIO modules for GLib, providing high-level network access, network diagnostic utilities, and TLS support. It is part of the GNOME project and is commonly used in Linux-based systems. | High-Level Network Access, Network Diagnostic Utilities, Tls Support | Glib, Network, Linux, Library | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.72.1 Faster: 2.72.1 |
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glibc | Ookami | glibc, the GNU C Library, is an essential part of most systems running the Linux kernel. It provides the necessary functionality for programs written in the C programming language to interact with the operating system and hardware. | Implementation Of The Standard C Library Functions, System Calls & Low-Level Interfaces, Dynamic Memory Allocation & Management, Thread Support & Synchronization, Localization Support | Library | Systems Programming | Computer & Information Sciences | C Library, Operating System, System Programming | Computer & Information Sciences | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 2.34 | System Library | |||||
glimmer | Anvil | Glimmer is system for finding genes in microbial DNA, especially the genomes of bacteria, archaea, and viruses. | Glimmer is a gene prediction software tool designed for microbial genomes. It uses a combination of statistics and hidden Markov models to predict potential protein-coding genes in DNA sequences. | 1. Gene prediction based on statistical models and hidden Markov models.\r 2. Specifically tailored for microbial genomes.\r 3. Supports both bacterial and archaeal genomes.\r 4. Provides predictions for protein-coding genes. |
Gene Prediction Tool | Microbial Genomics | Genomics | Gene Prediction, Microbial Genomes, Hidden Markov Models | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/glimmer | Anvil: 3.02 | Bioinformatics | ||||
glimmerhmm | Anvil | Glimmerhmm is a new gene finder based on a Generalized Hidden Markov Model. | GlimmerHMM is a software system for gene prediction in microbial genomes. It uses hidden Markov models to represent various aspects of a gene (e.g., start codons, stop codons, and exons) to accurately predict the locations of genes. | Gene Prediction In Microbial Genomes, Utilizes Hidden Markov Models, Predicts Start & Stop Codons, & Exons, Accurate Gene Location Prediction | Bioinformatics Tool | Microbial Genomics | Genomics | Gene Prediction, Microbial Genomes, Hidden Markov Models, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/glimmerhmm | Anvil: 3.0.4 | Gene Prediction | ||||
glm | Aces, Delta | The GLM (OpenGL Mathematics) library is a header-only C++ library designed for graphics software development, providing a wide range of mathematical structures and functions. Inspired by the syntax and conventions of GLSL (OpenGL Shading Language), GLM is particularly useful for OpenGL applications, offering functionality for vectors, matrices, and other complex mathematical operations needed in 3D graphics programming. | glm is a Python library for Generalized Linear Models (GLM) with support for exponential family distributions. | Implementation Of Generalized Linear Models (Glm), Support For Various Exponential Family Distributions, Estimation Of Model Parameters, Prediction & Inference, Model Evaluation & Diagnostics | https://glm.g-truc.net/0.9.9/api/modules.html | Library | Statistics & Probability | Python Library | https://glm.g-truc.net/0.9.9/ | Mathematics | https://github.com/g-truc/glm/blob/0.9.9.2/doc/manual.pdf https://www.youtube.com/watch?v=F0vUESYIrno https://web.engr.oregonstate.edu/~mjb/cs491/Handouts/GLM.1pp.pdf |
Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html |
Aces: 0.9.9.8 Delta: 0.9.9.8 |
Statistical Analysis | ||
glnexus | Anvil | Glnexus: Scalable gVCF merging and joint variant calling for population sequencing projects. | glnexus is a software tool for haplotype-aware variant calling and genotyping in large cohorts. | - Haplotype-aware variant calling\r - Genotyping in large cohorts\r - Detects complex variants\r - Scalable to handle large datasets\r - Supports VCF and BCF formats |
Bioinformatics Tool | Variant Calling, Genotyping, Haplotype-Aware, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/glnexus | Anvil: 1.4.1 | Genomic Data Analysis | ||||||
globalarrays | Aces, Faster | Global Arrays (GA) is a Partitioned Global Address Space (PGAS) programming model | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.8.2 Faster: 5.8, 5.8.2 |
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globus-cli | Aces, Faster | A Command Line Wrapper over the Globus SDK for Python, which provides an interface to Globus services from the shell, and is suited to both interactive and simple scripting use cases. | The globus-cli is a command-line interface tool that provides users with a way to interact with the Globus file transfer service directly from the terminal. It allows for managing transfers, accessing endpoints, and monitoring tasks efficiently through the command line interface. | Manage File Transfers, Access Endpoints, Monitor Tasks, Interact With Globus Service | Command Line Tool | Command-Line Interface, File Transfer Service, Data Management, Data Transfer | Other Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.6.0 Faster: 3.6.0 |
Tools | ||||||
glpk | Aces, Darwin, Expanse, Faster | The GLPK (GNU Linear Programming Kit) package is intended for solving large-scale linear programming (LP), mixed integer programming (MIP), and other related problems. It is a set of routines written in ANSI C and organized in the form of a callable library. Description Source: https://www.gnu.org/software/glpk/ |
GNU Linear Programming Kit (GLPK) is an open-source software package for solving large-scale linear programming (LP), mixed integer programming (MIP), and other related problems. It is designed with an emphasis on flexibility, portability, and ease of use. | Solves Large-Scale Linear Programming Problems, Supports Mixed Integer Programming & Related Problems, Offers Both A High-Level & Low-Level C Api For Problem Input & Output, Includes Tools For Post-Processing & Sensitivity Analysis | http://most.ccib.rutgers.edu/glpk.pdf | Mathematical Optimization | Operations Research | Applied Mathematics | Linear Programming, Optimization, Open-Source | https://www.gnu.org/software/glpk/ | Mathematics | https://martin-thoma.com/how-to-use-glpk/ https://en.wikibooks.org/wiki/GLPK/Using_the_GLPK_callable_library |
Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.0 Expanse: 2266Fla Faster: 4.65, 5.0 |
Solver | |
gmap | Anvil | Gmap is a genomic mapping and alignment program for mRNA and EST sequences. | GMAP (Genomic Mapping and Alignment Program) is a highly efficient and accurate software for mapping and aligning cDNA sequences to a genome, particularly useful in the analysis of RNA-seq data. It is designed to identify and map exon junctions in large genomes. | Efficient Mapping & Alignment Of Cdna Sequences To Genomes, Identification Of Exon Junctions, Suitable For Analyzing RNA-Seq Data, Highly Accurate Mapping Results | Bioinformatics Tool | Transcriptomics | Genomics | Bioinformatics, Computational Biology, Genomics, Transcriptomics, RNA-Seq | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gmap | Anvil: 2021.05.27, 2021.08.25 | Alignment Tool | ||||
gmap-gsnap | Expanse | GMAP and GSnap are splice-aware algorithms for mapping RNA-Seq reads to a genome. GMAP is a genomic mapping and alignment program while GSnap is a sensitive and accurate gapped read mapper. Both tools are commonly used in bioinformatics for RNA-Seq analysis. | Splice-Aware RNA-Seq Read Mapping, Alignment To A Reference Genome, Identification Of Novel Splice Sites, Support For Gapped Alignment | Analysis Tool | Genetics | Biological Sciences | RNA-Seq, Bioinformatics, Mapping, Alignment | Biological Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 2020-06-01 | Bioinformatics | |||||
gmp | Aces, Anvil, Darwin, Expanse, Faster, Kyric, Ookami | GNU MP is a portable library written in C for arbitrary precision arithmetic on integers, rational numbers, and floating-point numbers. It aims to provide the fastest possible arithmetic for all applications that need higher precision than is directly supported by the basic C types. Description Source: https://gmplib.org/manual/Introduction-to-GMP |
The GNU Multiple Precision Arithmetic Library (GMP) is a free library for arbitrary-precision arithmetic, operating on signed integers, rational numbers, and floating-point numbers. | 1. High-performance arithmetic functions for integers, rationals, and floating-point numbers. \r 2. Support for a wide range of mathematical operations including addition, subtraction, multiplication, division, exponentiation, and more. \r 3. Efficient memory management and algorithms for large numbers. \r 4. Portable and easy to use C library with interfaces available for various programming languages. |
https://gmplib.org/manual/ | Library | Other Mathematics | Pure Mathematics | Computational Software, Library, Mathematics, Software Development | https://gmplib.org/ | Mathematics | https://gmplib.org/manual/GMP-Basics https://gmplib.org/pi-with-gmp |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gmp Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 6.2.0, 6.2.1, 6.3.0 Anvil: 6.2.1 Expanse: 6.1.2 Faster: 6.1.2, 6.2.0, 6.2.1 |
Library | |
gmpy2 | Aces, Faster | GMP/MPIR, MPFR, and MPC interface to Python 2.6+ and 3.x | gmpy2 is a Python library for arbitrary-precision arithmetic within Python using the GMP and MPFR libraries. It provides efficient multiple-precision arithmetic in Python and supports both integer and floating-point arithmetic with arbitrary precision. | 1. High-performance multiple-precision arithmetic\r 2. Arbitrary-precision integer arithmetic\r 3. Arbitrary-precision floating-point arithmetic\r 4. Compatible with Python's math module\r 5. Supports complex numbers and mathematical functions |
Python Library | Python Library, Arbitrary-Precision Arithmetic, Gmp Library, Mpfr Library | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.1.2, 2.1.5 Faster: 2.1.0B4, 2.1.2, 2.1.5 |
Library | ||||||
gmt | Anvil | GMT is a collection of freely available command-line tools under the GNU LGPL that allows you to manipulate x, y and x, y, z data sets (filtering, trend fitting, gridding, projecting, etc.) and produce illustrations ranging from simple x-y plots, via contour maps, to artificially illuminated surfaces and 3-D perspective views in black/white or full color. Description Source: https://docs.generic-mapping-tools.org/latest/gmt.html |
The Generic Mapping Tools (GMT) is an open-source collection of command-line tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing PostScript illustrations ranging from simple x-y plots through contour maps to artificially illuminated surfaces and 3-D perspective views. GMT supports over 40 map projections and transformations and comes with support data such as coastlines, rivers, and political boundaries. | Manipulating Geographic & Cartesian Data Sets, Producing Postscript Illustrations, Supports Over 40 Map Projections & Transformations, Includes Coastlines, Rivers, & Political Boundaries Data | https://docs.generic-mapping-tools.org/latest/ | Command Line Tool | Mapping, Geographic Data, Cartesian Data, Illustration, Postscript, Map Projections | https://www.generic-mapping-tools.org/ | Earth & Environmental Sciences | https://docs.generic-mapping-tools.org/latest/tutorial.html https://www.generic-mapping-tools.org/workshops/#past-workshops |
Anvil: https://www.rcac.purdue.edu/software/gmt | Anvil: 6.1.0 | Visualization & Modeling | |||
gnu-parallel | Ookami | GNU parallel is a shell tool for executing jobs in parallel using one or more computers. A job can be a single command or a small script that has to be run for each of the lines in the input. The typical input is a list of files, a list of hosts, a list of users, a list of URLs, or a list of tables. A job can also be a command that reads from a pipe. GNU parallel can then split the input and pipe it into commands in parallel. Description Source: https://www.gnu.org/software/parallel/ |
https://www.gnu.org/software/parallel/sphinx.html | https://www.gnu.org/software/parallel/ | https://www.gnu.org/software/parallel/parallel_tutorial.html https://www.gnu.org/software/parallel/parallel_examples.html https://www.gnu.org/software/parallel/parallel_cheat.pdf https://zenodo.org/records/1146015 |
Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 20220922 | |||||||||
gnu9 | Kyric | https://gcc.gnu.org/onlinedocs/gcc-13.2.0/gcc/ | https://gcc.gnu.org/ | https://gcc.gnu.org/wiki/GettingStarted https://gcc-newbies-guide.readthedocs.io/en/latest/ https://www.geeksforgeeks.org/gcc-command-in-linux-with-examples/ |
Kyric: 9.3.0 | Compiler | ||||||||||
gnuplot | Aces, Anvil, Darwin, Delta, Expanse, Faster, Ookami | gnuplot is a command-driven plotting program. It can be used interactively to plot functions and data points in both two- and three-dimensional plots in many different styles and many different output formats. Gnuplot can also be used as a scripting language to automate generation of plots. Description Source: http://www.gnuplot.info/faq/#x1-60001.1 |
Gnuplot is a portable command-line driven graphing utility for Linux, OS/2, MS Windows, OSX, VMS, and many other platforms. It is capable of producing interactive plots and supports various output formats. | Gnuplot enables users to generate 2D and 3D plots, histograms, and animations. It supports a wide range of functions and data sources, with the ability to customize plot styles, labels, and axes. Gnuplot can be scripted for batch processing and supports various file formats for output including PNG, PDF, and SVG. It also allows users to combine multiple plots and perform complex data manipulations. | http://gnuplot.info/docs_5.5/Overview.html | Plotting & Data Visualization | Engineering | Graphing, Visualization, Data Analysis | https://gnuplot.sourceforge.net/ | Physical Sciences | https://gnuplot.sourceforge.net/screenshots/index.html#demos https://gnuplot.sourceforge.net/help.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gnuplot Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 5.4.4, 5.4.6, 5.4.8 Anvil: 5.4.2 Delta: 5.4.3 Expanse: Lfaey6L, Mfinpvw Faster: 5.2.8, 5.4.1, 5.4.2, 5.4.4 Ookami: 5.4.5 |
Graphing & Visualization Tools | ||
gnutls | Aces, Faster | GnuTLS is a secure communications library implementing the SSL, TLS and DTLS protocols and technologies around them. It provides a simple C language application programming interface (API) to access the secure communications protocols as well as APIs to parse and write X.509, PKCS #12, OpenPGP and other required structures. It is aimed to be portable and efficient with focus on security and interoperability. | GnuTLS is a secure communications library implementing the SSL, TLS and DTLS protocols, providing various cryptographic algorithms. | Implement Ssl, Tls, & Dtls Protocols, Support Various Cryptographic Algorithms, Secure Communication Library | Library | Security, Encryption, Networking | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.7.3 Faster: 3.7.3 |
Networking & Security | ||||||
go | Aces, Darwin, Expanse, Faster, Kyric, Ookami | Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language. Description Source: https://go.dev/doc/ |
https://go.dev/doc/ | https://go.dev/ | https://go.dev/doc/tutorial/getting-started https://go.dev/doc/tutorial/create-module https://go.dev/doc/tutorial/workspaces |
Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 1.18.3 Expanse: 1.15.1 Faster: 1.17.6, 1.18.3, 1.19.1, 1.20.5, 1.21.2 Ookami: 1.21.4 |
Programming Language | ||||||||
go-bootstrap | Kyric | go-bootstrap is a Go programming language template project that provides a starting point for building Go applications with a predefined project structure, configuration, and best practices. | 1. Predefined project structure for Go applications. 2. Built-in configuration setup. 3. Integration with popular Go libraries. 4. Simplifies starting a new Go project. | https://go.dev/doc/ | Template Project | Software Engineering, Systems, & Development | Go, Template, Project Structure, Best Practices | https://go.dev/ | Engineering & Technology | https://go.dev/doc/tutorial/getting-started https://go.dev/doc/tutorial/create-module https://go.dev/doc/tutorial/workspaces |
Development Tools | |||||
goatools | Anvil | Goatools is a Python library for Gene Ontology analyses. | Goatools is a Python library for exploring the Gene Ontology and determining the statistical significance of GO term enrichment in sets of genes or gene products. | Interpretation Of Gene Ontology (Go), Statistical Analysis Of Go Term Enrichment, Visualization Of Go Term Relationships, Integration With Biological Data Analysis Pipelines | Python Library | Genetics | Bioinformatics | Bioinformatics, Python Library, Gene Ontology, Enrichment Analysis, Biological Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/goatools | Anvil: 1.1.12, 1.2.3 | Library | ||||
gobff | Faster | gobff is a software tool for protein structure prediction based on the Fragment-Assembly Monte Carlo (FAMC) approach. It enables the modeling of protein structures by assembling fragments and refining the models using Monte Carlo simulations. | 1. Fragment-Assembly Monte Carlo (FAMC) based protein structure prediction\r 2. Fragment assembly for structure modeling\r 3. Monte Carlo simulations for model refinement\r 4. Ability to predict protein structures with high accuracy\r 5. User-friendly interface for easy input and visualization of results |
Computational Software | Protein Structure Prediction | Bioinformatics | Protein Structure Prediction, Fragment Assembly, Monte Carlo Simulations | Biological Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2020B, 2021A | Molecular Modeling | |||||
gobject-introspection | Aces, Faster | GObject introspection is a middleware layer between C libraries (using GObject) and language bindings. The C library can be scanned at compile time and generate metadata files, in addition to the actual native C library. Then language bindings can read this metadata and automatically provide bindings to call into the C library. Description Source: https://gi.readthedocs.io/en/latest/ |
GObject Introspection is a middleware layer between C libraries (using GObject) and language bindings. The goal is to make the C libraries accessible from scripting languages and other environments without the need for manual intervention. | Automated Generation Of Language Bindings For C Libraries, Allows Scripting Languages & Other Environments To Access C Libraries Easily, Eliminates Manual Intervention In Creating Language Bindings, Supports Gobject-Based Libraries | https://gi.readthedocs.io/en/latest/ | Library | Computer Science | Middleware, Language Bindings, Automation, Compatibility | https://gitlab.gnome.org/GNOME/gobject-introspection/ | Computer & Information Sciences | https://gitlab.gnome.org/GNOME/gobject-introspection/-/tree/main/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.68.0, 1.72.0, 1.74.0, 1.76.1 Faster: 1.63.1-Python-3.7.4, 1.64.0-Python-3.8.2, 1.66.1, ... |
Middleware | ||
golang | Darwin | Go, also commonly referred to as Golang, is a statically typed, compiled programming language designed at Google. It has a syntax similar to C, but with memory safety, garbage collection, structural typing, and CSP-style concurrency. | Memory Safety, Garbage Collection, Static Typing, Concurrency Support | Systems Programming | Programming Language, Software Development, Systems Programming | Computer & Information Sciences | Programming Language | |||||||||
gompi | Aces, Faster | Gompi is a software toolchain that combines the GNU Compiler Collection (GCC) for compiling software, OpenMPI for supporting parallel computing that requires message passing, and other essential libraries and tools for scientific computing. It is designed to facilitate the development and execution of high-performance computing (HPC) applications, especially those requiring robust parallel processing capabilities across clusters and grids. | Gompi is a parallel computing software tool that provides a set of compilers and libraries for running MPI (Message Passing Interface) programs on HPC (High Performance Computing) clusters. It aims to enhance the performance of parallel applications by optimizing communication and coordination between nodes in distributed computing environments. | Supports Mpi For Developing Parallel Applications, Includes Compilers & Libraries For Efficient Execution On Hpc Clusters, Optimizes Communication & Coordination Between Computing Nodes, Facilitates High-Performance Computing For Scientific & Engineering Simulations | Hpc, Parallel Computing, Mpi, Distributed Computing | https://docs.easybuild.io/api/easybuild/toolchains/gompi/ | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2020B, 2021A, 2021B, 2022A, 2022B, 2023A, 2023B, 2023.05, 2023.09 Faster: 2018B, 2019B, 2020A, 2020B, 2021A, 2021B, 2022A, 2022B, 2022.05, 2023A, 2023B |
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gompic | Aces, Faster | GNU Compiler Collection (GCC) based compiler toolchain along with CUDA toolkit, including OpenMPI for MPI support with CUDA features enabled. Description Source: https://hprc.tamu.edu/software/aces/ |
gompic is an open-source framework for simulating collective dynamics in soft matter systems with a focus on granular materials. It is designed to simulate the dynamics of large ensembles of particles undergoing complex interactions and can be used to study phenomena like granular flow, pattern formation, and self-organization. | 1. Simulation of granular systems with complex interactions.\r 2. Study of collective dynamics and emergent behaviors in soft matter.\r 3. Analysis of granular flow, pattern formation, and self-organization.\r 4. Open-source and customizable framework for research purposes. |
Research | Granular Materials Simulation | Other Physical Sciences | Simulation, Granular Materials, Collective Dynamics, Soft Matter | https://docs.easybuild.io/api/easybuild/toolchains/gompic/ | Physical Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2020B Faster: 2019B, 2020A, 2020B |
Simulation Framework | |||
googletest | Aces, Faster | GoogleTest is Google’s C++ testing and mocking framework. Description Source: https://google.github.io/googletest/ |
Google Test is a unit testing library for the C++ programming language. It is designed to be easy to write and understand tests, provides a rich set of assertions for verifying test expectations, and supports various testing styles. | Supports Various Testing Styles (Functional, Fixture, Parameterized, Etc.), Rich Set Of Assertion Macros For Validating Test Outcomes, Automatic Test Discovery & Registration, Integration With The Google C++ Testing Framework For Advanced Features, Reusable Test Fixtures For Common Setup & Teardown Operations | https://google.github.io/googletest/ | Library | Unit Testing, C++ Testing, Testing Library, Software Testing | https://github.com/google/googletest | Computer & Information Sciences | https://google.github.io/googletest/primer.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.11.0, 1.12.1, 1.13.0 Faster: 1.10.0, 1.11.0, 1.12.1, 1.13.0 |
Testing Framework | |||
gpaw | Anvil | GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE). | GPAW (Grid-based Projector-augmented wave method) is an efficient and accurate Density Functional Theory (DFT) code based on the projector-augmented wave (PAW) method. It is designed for simulating the electronic structure of atoms, molecules, and solid materials. | 1. Efficient and accurate electronic structure calculations using DFT.\r 2. Implementation of the projector-augmented wave (PAW) method.\r 3. Parallelized computations for high-performance calculations.\r 4. Support for a wide range of systems including atoms, molecules, and solid materials.\r 5. Ability to handle large systems with scalability.\r 6. Integration with various post-processing and analysis tools for comprehensive data analysis. |
https://wiki.fysik.dtu.dk/gpaw/documentation/documentation.html | Simulation | Materials Science | Condensed Matter Physics | Dft, Electronic Structure, Quantum Mechanics | https://gitlab.com/gpaw/gpaw | Physical Sciences | https://wiki.fysik.dtu.dk/gpaw/tutorialsexercises/tutorialsexercises.html https://wiki.fysik.dtu.dk/gpaw/documentation/basic.html |
Anvil: https://www.rcac.purdue.edu/software/gpaw | Anvil: 21.1.0 | Computational Chemistry | |
gperf | Aces, Faster, Ookami | GNU gperf is a perfect hash function generator. For a given list of strings, it produces a hash function and hash table, in form of C or C++ code, for looking up a value depending on the input string. The hash function is perfect, which means that the hash table has no collisions, and the hash table lookup needs a single string comparison only. Description Source: https://www.gnu.org/software/gperf/ |
GNU gperf is a perfect hash function generator tool that generates perfect hash functions for sets of keys, optimized for use in constructing a minimal perfect hash table. | 1. Generates perfect hash functions\r 2. Optimized for constructing minimal perfect hash tables\r 3. Supports sets of keys for hash function generation |
https://www.gnu.org/software/gperf/manual/gperf.html | Compiler/Generator | Software Engineering, Systems, & Development | Computer Science | Perfect Hash Function, Hash Table, Optimization, Gnu | https://www.gnu.org/software/gperf/ | Computer & Information Sciences | https://developer.ibm.com/tutorials/l-gperf/ https://www.math.utah.edu/docs/info/gperf_5.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 3.1 Faster: 3.1 Ookami: 3.1 |
Development Tool | |
gperftools | Aces, Faster, Ookami | Gperftools, formerly known as Google Performance Tools, is a collection of utilities for measuring and improving the performance of C++ programs. The suite includes a high-performance, multi-threaded malloc implementation, as well as tools for heap profiling, heap checking, and CPU profiling, making it valuable for developers looking to optimize their applications for speed and memory usage. | gperftools is a collection of performance analysis and profiling tools for C and C++ applications. It includes tools such as CPU and heap profilers, heap-checker, and a specialized CPU profiler for multithreaded programs. | 1. CPU profiler for single-threaded and multithreaded applications.\r 2. Heap profiler for memory allocation analysis.\r 3. Heap-checker for detecting memory leaks and memory errors.\r 4. Performance analysis tools to aid in optimizing code performance.\r 5. Scalable and efficient profiling capabilities for large-scale applications. |
https://github.com/gperftools/gperftools/wiki#documentation | Tool | Performance Analysis, Profiling, C/C++ | https://github.com/gperftools/gperftools | Engineering & Technology | https://github.com/gperftools/gperftools/wiki#example https://developer.ridgerun.com/wiki/index.php/Profiling_with_GPerfTools |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 2.10, 2.13 Faster: 2.12, 2.13, 2.14 Ookami: 2.9.1 |
Performance Analysis & Profiling Tools | |||
gpflow | Aces, Faster | GPflow is a package for building Gaussian process models in python, using TensorFlow. | GPflow is a Gaussian process library that uses TensorFlow for its core computational backend. It is a scalable, flexible, and modular Gaussian process framework for building probabilistic models. | 1. Supports Gaussian Processes (GPs) and Bayesian Neural Networks (BNNs)\r 2. High-level abstractions for creating complex models\r 3. Scalable inference methods for efficient computation\r 4. Integration with TensorFlow for automatic differentiation\r 5. Modular design for easy customization and extension |
Machine Learning, Probabilistic Programming, Gaussian Processes | Computer & Information Sciences, Artificial Intelligence & Intelligent Systems | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.9.0-Cuda-11.7.0-Tensorflow-2.11.0, 2.9.0-Cuda-11.7.0 Faster: 2.9.0-Cuda-11.7.0-Tensorflow-2.11.0 |
Computational Software | |||||||
gpu | Expanse | GPU, short for Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. In recent years, GPUs have been leveraged for general-purpose computing, allowing for massive parallel processing capabilities. | 1. Parallel processing: GPU architecture allows for thousands of cores to run multiple tasks simultaneously.\r 2. High-speed memory: They have dedicated high-speed memory to handle massive datasets efficiently.\r 3. Accelerated computing: GPUs speed up various computational tasks, including machine learning, simulations, and scientific calculations.\r 4. Programming support: GPU programming frameworks like CUDA and OpenCL enable developers to leverage GPU processing power in their applications. |
Hardware | Infrastructure & Instrumentation | Software, Computational Software, Hpc Tools, Gpu, Parallel Processing | Engineering & Technology, Computer & Information Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 0.15.4, 0.17.3B | Intermediate | ||||||
gpustat | Aces, Faster | Gpustat is a command-line utility that provides a quick and concise overview of the GPU status and usage information on systems with NVIDIA GPUs. It displays critical details such as GPU utilization, memory usage, temperature, and the list of processes currently using the GPUs, making it an essential tool for monitoring and managing GPU resources in real-time for both development and production environments. | gpustat is a Python library that gives an easy access to the GPU-related data, such as GPU utilization, memory usage, temperature, and power. It provides a command-line interface for quickly checking the status of GPUs in a system. | Retrieve Gpu Status Information, Monitor Gpu Utilization, Check Memory Usage & Temperature Of Gpus, Access Power Consumption Data, Simple Command-Line Interface For Quick Status Checks | https://github.com/wookayin/gpustat#usage | Library | Computer & Information Sciences | Computer Science | Gpu Monitoring, System Administration, Python Library, Command-Line Tool | https://github.com/wookayin/gpustat | Engineering & Technology | https://github.com/wookayin/gpustat#tips | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.1 Faster: 0.6.0, 1.0.0B1, 1.1 |
Data Management & Analytics | |
gpy | Faster | GPy is a Gaussian process framework in Python for implementing Gaussian processes. It offers tools for Gaussian process regression, classification, optimization, and more. | Gaussian Process Regression, Gaussian Process Classification, Gaussian Process Optimization, Implementation In Python | Data Analysis | Machine Learning, Data Analysis, Python, Gaussian Processes | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.10.0 | Library | |||||||
gpytorch | Faster | GPyTorch is a Gaussian process library implemented using PyTorch. It is designed for scalable and flexible Gaussian process models, with a focus on deep learning integration. | 1. Scalable Gaussian process models\r 2. Integration with PyTorch for deep learning\r 3. Flexibility in model construction\r 4. Efficient computation through GPU acceleration\r 5. Bayesian optimization and kernel learning capabilities |
Python Library | Machine Learning, Gaussian Processes, Deep Learning | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.6.0 | Machine Learning Library | |||||||
graalvm | Faster | GraalVM is a high-performance runtime providing significant improvements in application performance and efficiency. It is designed to run applications written in Java, JavaScript, LLVM-based languages, Python, Ruby, R, and other dynamic languages. | Support For Multiple Languages Like Java, Javascript, Python, Ruby, R, & Llvm-Based Languages, High-Performance Runtime With Enhanced Application Performance, Just-In-Time Compilation For Improved Efficiency, Polyglot Capabilities Allowing Interoperability Between Different Languages, Native Image Generation For Faster Startup & Lower Memory Consumption | Compiler/Runtime | Software Development, Runtime Environment, Polyglot Programming, Just-In-Time Compilation, Native Image Generation | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 21.3.0, 22.2.0 | Development Tools | |||||||
grace | Expanse | Grace is a WYSIWYG 2D plotting tool for the X Window System and M*tif. The program renders high-quality plots for scientific and engineering applications. | Some core features of Grace include the ability to create both 2D and 3D plots, support for various plot types (e.g., line, scatter, bar), customizable plot properties (e.g., colors, labels, legends), interactive plot manipulation, export options for different file formats, and scripting capabilities for automation. | Graphing/Plotting | Plotting Tool, Scientific Visualization, 2D Plotting, Engineering Applications | Physical Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: 5.1.25 | Data Visualization/Plotting | |||||||
gradle | Faster | Gradle is an open-source build automation tool focused on flexibility and performance. It uses a Groovy-based domain-specific language (DSL) to define build configurations, allowing for highly customizable build processes. | Support For Multi-Project Builds, Dependency Management, Plugins For Various Tasks, Incremental Builds, Extensible Through Groovy Dsl | Tools | Build Automation, Dependency Management, Java, Groovy | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 6.9.1 | Build Tools | |||||||
grads | Anvil | GrADS (Grid Analysis and Display System) is an interactive desktop tool that is used for easy access, manipulation, and visualization of earth science data. It is particularly popular in meteorology and climatology for analyzing and plotting meteorological data. | Data Visualization, Data Analysis, Grid Analysis, Time Series Analysis, Meteorological Data Processing, Customizable Plots | Desktop Application | Data Visualization, Meteorology, Climatology, Earth Science, Data Analysis | Earth & Environmental Sciences | Anvil: https://www.rcac.purdue.edu/software/grads | Anvil: 2.2.1 | Visualization Software | |||||||
graphblas | Aces | SuiteSparse:GraphBLAS is a complete implementation of the GraphBLAS standard, which defines a set of sparse matrix operations on an extended algebra of semirings using an almost unlimited variety of operators and types. When applied to sparse adjacency matrices, these algebraic operations are equivalent to computations on graphs. | GraphBLAS is a collection of high-performance linear algebraic operations specifically designed for sparse graphs and matrices. | 1. Extensive set of linear algebra operations for manipulating graph structures and sparse matrices.\r 2. Optimized for performing calculations on large-scale graphs efficiently.\r 3. Provides a flexible framework for developing graph algorithms and applications.\r 4. Supports a wide range of graph analytics and machine learning tasks.\r 5. Designed for parallel and distributed computing environments. |
Library | Graph, Linear Algebra, Sparse Matrices | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 8.2.1 | Computational Software | ||||||
graphene | Aces, Faster | Graphene is a software library that provides a collection of utilities for handling 2D graphics and computational geometry, focusing on providing a thin layer of types and functions that are useful for graphics applications. It is designed to be efficient and lightweight, offering capabilities such as matrices, vectors, rectangles, and quaternions for operations like transformations and intersections, making it a valuable tool for developers working on graphical interfaces, animations, and other visual computations. | Graphene is a Python library for building GraphQL APIs fast and easily. | 1. Simplifies the process of building GraphQL APIs\r 2. Integrates seamlessly with Python-based web frameworks\r 3. Provides a simple and elegant syntax for defining GraphQL schemas\r 4. Supports auto-generated documentation |
https://ebassi.github.io/graphene/docs/ | Library | Python Library, Graphql | https://ebassi.github.io/graphene/ | Computer & Information Sciences | https://github.com/ebassi/graphene/wiki/Using-Graphene-from-Python | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.10.8 Faster: 1.10.8 |
Web Development | |||
graphicsmagick | Aces, Faster | GraphicsMagick is a robust and efficient software suite for processing images, offering a rich set of command-line utilities and programming APIs for reading, writing, and manipulating an array of image formats. Renowned for its performance and quality, it supports tasks such as resizing, rotating, and color adjustments, making it a versatile tool for developers, photographers, and graphic artists in automating image processing workflows. | GraphicsMagick is a robust collection of tools and libraries that offers a comprehensive range of image processing capabilities. It provides a powerful utility for dynamically reading, writing, and modifying images for over 88 major formats. | Support For Over 88 Major Image Formats, Image Processing Capabilities, Extensive Command-Line Tools, Efficient Handling Of Large Images, Color Management & Color Space Conversion | http://www.graphicsmagick.org/GraphicsMagick.html | Image Processing Software | Image Processing, Graphics, Media Editing, Command-Line Tools | http://www.graphicsmagick.org/ | Other Computer & Information Sciences | http://www.graphicsmagick.org/programming.html https://www.tutorialspoint.com/graphicsmagick-a-powerful-image-processing-cli-tool-for-linux https://www.tecmint.com/graphicsmagick-image-processing-cli-tool-for-linux/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.3.36 Faster: 1.3.36 |
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graphite2 | Aces, Faster | Graphite is a “smart font” system developed specifically to handle the complexities of lesser-known languages of the world. Description Source: https://graphite.sil.org/ |
Graphite is a system that can be used to create 'smart fonts' capable of displaying writing systems with various complex behaviors. Graphite fonts are capable of providing contextual forms, reordering, ligatures, and other advanced typographic behavior. | 1. Support for creating 'smart fonts' with advanced typographic behavior\r 2. Capable of displaying writing systems with complex behaviors\r 3. Provides features such as contextual forms, ligatures, and reordering\r 4. Enables the creation of fonts for languages/scripts that require special typographic handling |
https://graphite.sil.org/assets/resources/GDL.pdf | Library | Font Technology | Computer Science | Font Rendering, Typography, Smart Fonts | https://graphite.sil.org/ | Computer & Information Sciences | https://graphite.sil.org/graide_tutorial | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.3.14 Faster: 1.3.14 |
Font Rendering Engine | |
graphlan | Anvil | Graphlan is a software tool for producing high-quality circular representations of taxonomic and phylogenetic trees. | Graphlan is a software tool used for the visualization and annotation of phylogenetic trees and their associated metadata. It allows users to create high-quality graphical representations of phylogenetic trees with customizable features and options. | Visualization Of Phylogenetic Trees, Annotation Of Trees With Metadata, Customizable Features For Tree Display, Support For Complex Tree Layouts, Interactive Viewing Capabilities | Graph Visualization | Phylogenetics, Tree Visualization, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/graphlan | Anvil: 1.1.3 | Data Visualization | ||||||
graphmap | Anvil | Graphmap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data. | GraphMap is a software tool for mapping next-generation sequencing data to a reference genome using the graphical FM index (GFM). It is designed to efficiently align large sets of short sequencing reads generated by modern high-throughput sequencing technologies. | 1. Utilizes graphical FM index (GFM) for efficient read alignment\r 2. Designed for mapping large sets of short sequencing reads\r 3. Supports various next-generation sequencing data types\r 4. High performance and parallel processing capabilities |
Bioinformatics Tool | Genomics | Alignment, Sequencing, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/graphmap | Anvil: 0.6.3 | Sequence Alignment | |||||
graphviz | Aces, Expanse, Faster | Graphviz is open source graph visualization software. Graph visualization is a way of representing structural information as diagrams of abstract graphs and networks. It has important applications in networking, bioinformatics, software engineering, database and web design, machine learning, and in visual interfaces for other technical domains. | Graphviz is open source graph visualization software. It is used for creating structured diagrams such as flowcharts, network diagrams, and more. | Automatic Layout Algorithms For Visualization, Support For Various Input Formats Including Dot Language, Customizable Node Shapes, Colors, & Styles, Ability To Render Graphs In Various Output Formats Such As Png, Pdf, Svg | Data Visualization | Graph Visualization, Diagramming, Open Source Software | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.0.0 Expanse: Rsjj7Kb Faster: 2.47.2, 2.50.0, 8.1.0 |
Visualization Tool | ||||||
graphviz-python | Aces | Simple Python interface for Graphviz | graphviz-python is a Python library for creating and rendering graph visualizations using Graphviz. It provides a simple interface to create and manipulate graphs and visualize them in various formats. | 1. Generate and customize graphs programmatically. 2. Render graphs in various formats such as PNG, PDF, SVG, etc. 3. Support for complex graph structures and layouts. | Visualization Tool | Graph Visualization, Python Library, Network Analysis | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.20.1 | Library | ||||||
grass | Aces, Faster | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 8.2.0, 8.3.1 Faster: 8.2.0 |
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greenlet | Aces | greenlets are lightweight coroutines for in-process sequential concurrent programming. Description Source: https://pypi.org/project/greenlet/ |
Greenlet is a lightweight library that allows micro-threads to be utilized in a concurrent programming fashion within a single process. It provides a simple way to implement coroutines in Python. | Efficient Micro-Threads (Coroutines), Concurrency Within A Single Process, Context Switching Between Greenlets, Simple Api For Implementing Coroutines | https://greenlet.readthedocs.io/en/latest/ | Programming | Python Library, Concurrency, Coroutines | https://github.com/python-greenlet/greenlet | Computer & Information Sciences | https://greenlet.readthedocs.io/en/latest/greenlet.html https://greenlet.readthedocs.io/en/latest/gui_example.html#gui-example |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 2.0.2 | Library | |||
gridss | Anvil | Gridss is a module software suite containing tools useful for the detection of genomic rearrangements. | Gridss is a structural variant caller that identifies complex, nested, and discontinuous structural variations from high-throughput DNA sequencing data. It aims to improve the detection of genomic rearrangements, such as insertions, deletions, inversions, and translocations. | 1. Structural variant calling from DNA sequencing data\r 2. Identification of complex, nested, and discontinuous structural variations\r 3. Detection of genomic rearrangements like insertions, deletions, inversions, and translocations |
Tool | Genomic Structural Variation | Genetics | Structural Variant Calling, DNA Sequencing, Genomic Rearrangements | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gridss | Anvil: 2.13.2 | Bioinformatics | ||||
groff | Aces, Faster | groff (GNU roff) is a typesetting system that reads plain text input files that include formatting commands to produce output in PostScript, PDF, HTML, or DVI formats or for display to a terminal. Formatting commands can be low-level typesetting primitives, macros from a supplied package, or user-defined macros. All three approaches can be combined. Description Source: https://www.gnu.org/software/groff/ |
Groff (GNU troff) is a typesetting system that reads plain text mixed with formatting commands and produces formatted output. It's a modern implementation of the classic Unix troff typesetting system. | Typesetting System, Formatting Commands, Formatted Output, Unix Troff Implementation | https://www.gnu.org/software/groff/manual/groff.html.node/index.html | Typesetting System | Typesetting, Text Formatting, Unix Utilities | https://www.gnu.org/software/groff/ | Computer & Information Sciences | https://www.gnu.org/software/groff/manual/groff.html.node/Introduction.html https://www.gnu.org/software/groff/manual/groff.html.node/Basics.html https://www.systutorials.com/docs/linux/man/7-groff/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.22.4, 1.23.0 Faster: 1.22.4 |
Document Preparation System | |||
gromacs | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Kyric, Ookami, Stampede3 | GROMACS (GROningen MAchine for Chemical Simulations) is a molecular dynamics package primarily designed for simulations of proteins, lipids and nucleic acids. It was originally developed in the Biophysical Chemistry department of University of Groningen, and is now maintained by contributors in universities and research centers across the world. | GROMACS (GROningen MAssive Parallel MD for Molecular Dynamics) is a versatile package for molecular dynamics simulations with a strong emphasis on high-performance computing capabilities. | Efficient Algorithms For Molecular Dynamics Simulations, Optimized For Performance On Cpus, Gpus, & Other Accelerators, Support For Various Force Fields & Integrators, Analysis Tools For Processing Simulation Output Data, Extensive Community Support & Documentation | https://manual.gromacs.org/current/index.html | Molecular Dynamics Software | Biophysics | Chemistry | Molecular Dynamics, Simulation, High Performance Computing, Biomolecular Systems | https://www.gromacs.org/ | Biological Sciences | https://tutorials.gromacs.org/ https://www.gromacs.org/workshop.html https://www.gromacs.org/tutorial_webinar.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gromacs Bridges-2: https://www.psc.edu/resources/software/gromacs Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 2021.5-Cuda-11.4.1-Plumed-2.8.0, 2023.1-Cuda-11.7.0, 2023.1-Cuda-12.2.0, 2023.3-Cuda-11.8.0, ... Anvil: 2020.2, 2021, 2021.2, 2021.3 Bridges-2: 2018, 2020.2-Cpu, 2020.4-Gpu Delta: 2022.5.Cuda, 2022.5.X86_64 Expanse: Rspmhnj-Omp, Sbq2Qrc-Omp Faster: 2020.5-Ramd-2.0, 2021-Constantph-2022.05.25, 2021, 2021.3, 2021.5-Cuda-11.4.1-Plumed-2.8.0, ... Ookami: Gcc12.1/2022.3 Stampede-3: 2023.3, 2024 |
Simulation Software | |
grpc | Faster | gRPC is a high-performance, open-source remote procedure call (RPC) framework that enables client and server applications to communicate transparently, efficiently, and securely across distributed systems. | 1. Supports multiple programming languages such as C++, Java, Python, Go, etc.\r 2. Uses Protocol Buffers as the interface definition language for defining services and message types.\r 3. Bi-directional streaming, flow control, deadline propagation, and authentication are key features.\r 4. Supports synchronous and asynchronous programming models. |
Library/Framework | Rpc, Distributed Systems, Communication | Computer & Information Sciences, Software Engineering, Systems, & Development | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.44.0 | Middleware | |||||||
gsd-vmd | Faster | GSD-VMD is a tool for visualizing and analyzing simulation trajectories stored in the GSD file format, a hierarchical file format built for high-performance molecular simulation workflows. It integrates with the popular VMD visualization software to provide a powerful toolset for molecular dynamics analysis. | 1. Visualization of simulation trajectories in the GSD file format.\r 2. Analysis of molecular simulation data.\r 3. Integration with VMD for advanced visualization capabilities.\r 4. Support for high-performance molecular simulation workflows. |
Molecular Dynamics, Simulation Analysis, Trajectory Visualization | Other Natural Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: V0.4.0 | |||||||||
gseapy | Anvil | Gseapy is a python wrapper for GESA and Enrichr. | GSEApy is a Python library for Gene Set Enrichment Analysis (GSEA) and various enrichment analysis methods to interpret gene expression data. | Supports Gene Set Enrichment Analysis (Gsea), Offers Various Enrichment Analysis Methods, Allows Interpretation Of Gene Expression Data, Provides Tools For Pathway & Network Analysis | Library | Gene Expression Analysis | Bioinformatics | Bioinformatics, Computational Biology, Python Library, Enrichment Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gseapy | Anvil: 0.10.8 | Analysis Tool | ||||
gsl | Aces, Anvil, Darwin, Delta, Expanse, Faster, Stampede3 | The GNU Scientific Library (GSL) is a numerical library for C and C++ programmers. The library provides a wide range of mathematical routines such as random number generators, special functions and least-squares fitting. | The GNU Scientific Library (GSL) is a numerical library for C and C++ programmers. It provides a wide range of mathematical routines such as special functions, linear algebra, interpolation, numerical integration, random numbers, and more. | 1. Implementation of a comprehensive set of mathematical functions\r 2. High-performance numerical routines\r 3. Modular structure for easy integration into C and C++ applications\r 4. Extensive documentation and examples\r 5. Open-source and free to use |
https://www.gnu.org/software/gsl/doc/html/index.html | Library | Mathematics | Numerical Library, Mathematical Functions, C Programming, C++ Programming | https://www.gnu.org/software/gsl/ | Other Mathematics | https://www.gnu.org/software/gsl/doc/html/usage.html https://www.gnu.org/software/gsl/doc/html/err.html#examples https://www.gnu.org/software/gsl/doc/html/linalg.html#examples |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gsl Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 2.6, 2.7 Anvil: 2.4 Delta: 2.7.1 Expanse: Aji2Yx5, Gfpesxa, Ix3Kgnc, ... Faster: 2.6, 2.7 Stampede-3: 2.7.1 |
Numerical Library | ||
gslib | Aces, Faster | A sparse communication library. | gslib is an open-source and free collection of Fortran 77 subroutines for geostatistical applications. | gslib provides a wide range of geostatistical tools for variogram modeling, kriging, and spatial data analysis. It also includes utilities for data transformation and visualization of spatial data. | Geospatial Analysis Tool | Geostatistics | Geoscience | Geostatistics, Fortran 77, Spatial Data, Variogram Modeling, Kriging | Earth & Environmental Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.0.8 Faster: 1.0.8 |
Library | ||||
gst-plugins-bad | Aces, Faster | GStreamer Bad Plug-ins is a set of plug-ins that aren't up to par compared to the rest. They might be close to being good quality, but they're missing something - be it a good code review, some documentation, a set of tests, a real live maintainer, or some actual wide use. Description Source: https://gstreamer.freedesktop.org/modules/gst-plugins-bad.html |
gst-plugins-bad is a collection of GStreamer plugins and elements that are not of high quality, experimental, or have not been tested well. These plugins are considered 'bad' due to various reasons such as being incomplete, breaking or lacking proper documentation. | 1. Provides a variety of GStreamer plugins and elements.\r 2. Experimental plugins for testing new functionalities.\r 3. Plugins that are incomplete or lack proper testing.\r 4. Supplement to the GStreamer plugins base. |
https://gitlab.freedesktop.org/gstreamer/gstreamer/-/tree/main/subprojects/gst-plugins-bad/docs | Plugin | Multimedia, Plugin, Gstreamer | https://gstreamer.freedesktop.org/modules/gst-plugins-bad.html | Computer & Information Sciences | https://gstreamer.freedesktop.org/documentation/tutorials/basic/index.html?gi-language=c https://gstreamer.freedesktop.org/documentation/tutorials/table-of-concepts.html?gi-language=c https://gstreamer.freedesktop.org/documentation/tutorials/index.html?gi-language=c |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.20.2 Faster: 1.20.2 |
Multimedia | |||
gst-plugins-base | Aces, Faster | GStreamer Base Plug-ins is a well-groomed and well-maintained collection of GStreamer plug-ins and elements, spanning the range of possible types of elements one would want to write for GStreamer. It also contains helper libraries and base classes useful for writing elements. A wide range of video and audio decoders, encoders, and filters are included. Description Source: https://gstreamer.freedesktop.org/modules/gst-plugins-base.html |
gst-plugins-base is a collection of GStreamer plugins and elements, which serve as the base for GStreamer. These plugins provide essential functionalities for building audio and video processing pipelines in GStreamer-based applications. | 1. Support for various container formats like AVI, QuickTime, Matroska, etc. \r 2. Decoding and encoding support for a wide range of audio and video codecs. \r 3. Basic elements for audio and video playback, recording, streaming, and manipulation. \r 4. Integration with hardware-accelerated video decoding and encoding through VA-API, VDPAU, etc. |
https://gitlab.freedesktop.org/gstreamer/gstreamer/-/tree/main/subprojects/gst-plugins-base/docs | Plugin | Multimedia Processing | Computer Science | Audio Processing, Video Processing, Multimedia Framework | https://gstreamer.freedesktop.org/modules/gst-plugins-base.html | Computer & Information Sciences | https://gstreamer.freedesktop.org/documentation/tutorials/basic/index.html?gi-language=c https://gstreamer.freedesktop.org/documentation/tutorials/table-of-concepts.html?gi-language=c https://gstreamer.freedesktop.org/documentation/tutorials/index.html?gi-language=c |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.18.5, 1.20.2, 1.22.1 Faster: 1.16.2, 1.18.4, 1.18.5, 1.20.2, 1.22.1 |
Library | |
gstreamer | Aces, Anvil, Faster | GStreamer is a library for constructing graphs of media-handling components. The applications it supports range from simple Ogg/Vorbis playback, audio/video streaming to complex audio (mixing) and video (non-linear editing) processing. Description Source: https://gstreamer.freedesktop.org/ |
GStreamer is a multimedia framework that allows the construction of graphs of media-handling components, ranging from simple Ogg/Vorbis playback to complex audio (mixing) and video (non-linear editing) processing. It is designed to be easily extended with new plugins that provide new functionality. | 1. Support for a wide range of media formats and protocols. 2. Modular architecture that allows flexible construction of multimedia pipelines. 3. Extensive plugin architecture for additional features and format support. 4. Cross-platform compatibility. 5. Open-source and actively developed community. | https://gstreamer.freedesktop.org/documentation/ | Framework | Multimedia, Framework, Media Processing, Audio, Video | https://gstreamer.freedesktop.org/ | Computer & Information Sciences | https://gstreamer.freedesktop.org/documentation/tutorials/basic/index.html?gi-language=c https://gstreamer.freedesktop.org/documentation/tutorials/table-of-concepts.html?gi-language=c https://gstreamer.freedesktop.org/documentation/tutorials/index.html?gi-language=c |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/gstreamer Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.18.5, 1.20.2, 1.22.1, 1.22.5 Anvil: 1.16.1 Faster: 1.16.2, 1.18.4, 1.18.5, 1.20.2, 1.22.1 |
Media Processing | |||
gtdbtk | Anvil | GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes based on the Genome Database Taxonomy GTDB. | Anvil: https://www.rcac.purdue.edu/software/gtdbtk | Anvil: 1.7.0, 2.1.0 | ||||||||||||
gthumb | Delta | gthumb is an image viewer and browser for the GNOME desktop environment. It also includes features for organizing and managing images. | Image Viewing & Browsing, Image Organization & Management, Basic Editing Functionalities, Slideshow Creation, Batch Processing Of Images | Desktop Application | Image Viewer, Image Browser, Image Management | Other Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 3.12.0 | Image Viewer/Editor | |||||||
gtk+ | Faster | GTK+ is a multi-platform toolkit for creating graphical user interfaces. It offers a comprehensive set of widgets for building GUIs and provides tools for interaction with the user interface. GTK+ is widely used in software development for creating desktop applications with a consistent look and feel across different operating systems. | Cross-Platform Compatibility, Extensive Widget Library, Support For Numerous Programming Languages, Customizable Theming, Accessibility Features, Internationalization & Localization Support | Toolkit | Gui Toolkit, Graphical User Interface, Desktop Application Development | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 3.24.13, 3.24.23 | Application Software | |||||||
gtk2 | Aces, Faster | GTK is a widget toolkit. Each user interface created by GTK consists of UI elements known as widgets. The GTK programming interface is based on Object Orientation; widgets are organized in a hierarchy of classes—for instance, the window widget is also a specialised container, called a “bin”, that can hold at most one child widget. A window will be able to use functions that pertain to the widget, container, bin, and window classes. Description Source: https://www.gtk.org/ |
GTK2 is a cross-platform widget toolkit for creating graphical user interfaces. It is used in a variety of applications to provide a user-friendly interface. | 1. Provides a set of graphical control elements\r 2. Supports event-driven programming\r 3. Easily customizable and themable\r 4. Allows for creating interactive and responsive GUIs\r 5. Cross-platform compatibility |
https://developer-old.gnome.org/gtk2/stable/index.html | Gui Toolkit | Sciences | Biology | Gui, Widget Toolkit, Cross-Platform | https://www.gtk.org/ | Computer & Information Sciences | https://www.gtk.org/docs/getting-started/hello-world/ https://www.gtk.org/docs/getting-started/ https://www.gtk.org/docs/language-bindings/python/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.24.33 Faster: 2.24.33 |
Library | |
gtk3 | Aces, Faster | GTK is a widget toolkit. Each user interface created by GTK consists of UI elements known as widgets. The GTK programming interface is based on Object Orientation; widgets are organized in a hierarchy of classes—for instance, the window widget is also a specialised container, called a “bin”, that can hold at most one child widget. A window will be able to use functions that pertain to the widget, container, bin, and window classes. Description Source: https://www.gtk.org/ |
GTK3 is a widely-used toolkit for building graphical user interfaces and desktop applications. It provides a comprehensive set of tools and libraries for creating interactive and visually appealing applications across multiple platforms. | Cross-Platform Compatibility, Extensive Widget Toolkit, Customizable Themes & Styles, Support For Various Programming Languages | https://docs.gtk.org/gtk3/ | Development Toolkit | Sciences | Biology | Gui Toolkit, Desktop Application Development, Cross-Platform Development, User Interface Design | https://www.gtk.org/ | Computer & Information Sciences | https://www.gtk.org/docs/getting-started/hello-world/ https://www.gtk.org/docs/getting-started/ https://www.gtk.org/docs/language-bindings/python/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.24.31, 3.24.35, 3.24.37 Faster: 3.24.31, 3.24.33, 3.24.35, 3.24.37 |
Framework/Library | |
gtk4 | Aces, Faster | GTK is a widget toolkit. Each user interface created by GTK consists of UI elements known as widgets. The GTK programming interface is based on Object Orientation; widgets are organized in a hierarchy of classes—for instance, the window widget is also a specialised container, called a “bin”, that can hold at most one child widget. A window will be able to use functions that pertain to the widget, container, bin, and window classes. Description Source: https://www.gtk.org/ |
GTK4 is a multi-platform toolkit for creating graphical user interfaces. It is used for developing applications with a consistent look and feel across different operating systems. | Cross-Platform Support, Customizable Themes & Styling, Support For Various Programming Languages, Integration With Popular Programming Languages & Development Environments | https://docs.gtk.org/gtk4/ | Development Tool | Sciences | Biology | Gui Toolkit, Cross-Platform Development, User Interface Design | https://www.gtk.org/ | Computer & Information Sciences | https://www.gtk.org/docs/getting-started/hello-world/ https://www.gtk.org/docs/getting-started/ https://www.gtk.org/docs/language-bindings/python/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.7.0 Faster: 4.7.0 |
Graphical User Interface (Gui) Toolkit | |
gts | Aces, Faster | The GNU Triangulated Surface Library (GTS) is a library for constructing and manipulating surface meshes, particularly 3D triangulated surfaces. It offers data structures and algorithms for tasks like mesh simplification, refinement, and more. | GNU Triangulated Surface Library (GTS) is a free library for computational geometry. It includes many useful functions for calculating surface properties and constructing complex surfaces using triangulations. | Computation Of Geometric Surface Properties, Triangulation Of Complex Surfaces, Support For 2D & 3D Geometric Data Structures, Mesh Generation & Manipulation Tools | https://gts.sourceforge.net/reference/book1.html | Computational Software | Computational Geometry, Surface Properties, Mesh Generation | https://gts.sourceforge.net/ | Computer & Information Sciences | https://github.com/lsaavedr/gts/tree/master/examples https://gts.sourceforge.net/samples.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.7.6 Faster: 0.7.6 |
Library | |||
gubbins | Anvil | Gubbins is an algorithm that iteratively identifies loci containing elevated densities of base substitutions while concurrently constructing a phylogeny based on the putative point mutations outside of these regions. | Gubbins is a software tool for the analysis of bacterial recombination data. It identifies recombination events in bacterial populations from whole-genome sequence data. | 1. Detection of recombination events in bacterial populations\r 2. Analysis of whole-genome sequence data\r 3. Identification of genomic regions under recombination\r 4. Visualization of recombination events\r 5. Phylogenetic tree construction |
Bioinformatics | Bacterial Recombination, Whole-Genome Sequencing, Population Genetics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/gubbins | Anvil: 3.2.0, 3.3 | |||||||
guile | Aces, Faster | Guile is a programming language, designed to help programmers create flexible applications that can be extended by users or other programmers with plug-ins, modules, or scripts. | Guile is an implementation of the Scheme programming language, providing a flexible and embeddable scripting environment for applications. It aims to be a platform for creating applications and libraries that require customizations and extensibility. | Guile offers a powerful Scheme interpreter, a reliable extension language for C and C++ programs, an interactive environment for Scheme development, a large standard library, and a module system that supports extension scripts and plugins. | Interpreter | Programming Language, Scripting Language, Embeddable, Customizable | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.0.7 Faster: 1.8.8, 3.0.7 |
Programming Language | ||||||
guppy | Anvil, Bridges-2 | Guppy is a data processing toolkit that contains the Oxford Nanopore Technologies' production basecalling algorithms and several bioinformatic post-processing features. It is run from the command line in Windows, Mac OS, and on multiple Linux platforms. Guppy is also integrated with our sequencing instrument software, MinKNOW, and a subset of Guppy features are available via the MinKNOW UI. A selection of configuration files allows basecalling of DNA and RNA libraries made with Oxford Nanopore Technologies’ current sequencing kits, in a range of flow cells. Description Source: https://community.nanoporetech.com/docs/prepare/library_prep_protocols/Guppy-protocol/v/gpb_2003_v1_revax_14dec2018/guppy-software-overview |
Guppy is a basecaller developed by Oxford Nanopore Technologies for processing raw electrical signal data generated by their nanopore sequencing devices. It is designed to convert the raw signal data into nucleotide sequences, providing a platform for downstream analysis in genomics research. | Basecalling Of Raw Electrical Signal Data From Nanopore Sequencing Devices, Conversion Of Raw Signal Data Into Nucleotide Sequences, Support For Real-Time Basecalling During Sequencing Runs, Integration With Oxford Nanopore Technologies' Sequencing Platforms, Compatibility With Various Sequencing Protocols | https://community.nanoporetech.com/docs/prepare/library_prep_protocols/Guppy-protocol/v/gpb_2003_v1_revax_14dec2018/expert-settings | Basecaller | Next-Generation Sequencing | Genomics | Bioinformatics, Sequencing, Nanopore Sequencing, Genomics, DNA Sequencing | https://community.nanoporetech.com/docs/prepare/library_prep_protocols/Guppy-protocol/v/gpb_2003_v1_revax_14dec2018/guppy-software-overview | Biological Sciences | https://community.nanoporetech.com/docs/prepare/library_prep_protocols/Guppy-protocol/v/gpb_2003_v1_revax_14dec2018/setting-up-a-run-configurations-and-parameters | Anvil: https://www.rcac.purdue.edu/software/guppy Bridges-2: https://www.psc.edu/resources/software/guppy |
Anvil: 6.0.1, 6.5.7 Bridges-2: 6.0.0, 6.5.7 |
Bioinformatics Tool | |
guppy-gpu | Bridges-2 | Guppy is a basecaller software for Oxford Nanopore sequencing data. The GPU version utilizes the power of graphics processing units to accelerate the basecalling process for faster and more efficient analysis of sequencing data. | 1. Utilizes GPU acceleration for rapid basecalling\r 2. Optimized for Oxford Nanopore sequencing data\r 3. Supports real-time sequencing data analysis\r 4. Provides high-throughput processing capabilities |
Bioinformatics Tool | Genetics | Bioinformatics | Basecaller, Oxford Nanopore, Sequencing, Gpu Acceleration | Biological Sciences | Bridges-2: https://www.psc.edu/resources/software/guppy-gpu | Bridges-2: 6.0.1 | Analysis Tool | |||||
gurobi | Anvil, Bridges-2, Delta | Gurobi optimizer is a solver for mathematical programming thhat includes a linear programming solver, a mixed-integer linear programming solver, a mixed-integer quadratic programming solver, a quadratic programming solver, a quadratically constrained programming solver, and a mixed-integer quadratically constrained programming solver. Description Source: https://www.gurobi.com/solutions/gurobi-optimizer/ |
Gurobi Optimization is a high-performance mathematical programming solver for linear programming (LP), mixed-integer programming (MIP), and other related optimization problems. | Some core features of Gurobi include advanced performance (fast and scalable algorithms), support for a variety of programming languages (Python, MATLAB, C++, etc.), ability to handle complex optimization models, interactive visualizations, and extensive documentation and user support. | https://www.gurobi.com/documentation/ | Solver | Optimization, Mathematical Programming, Linear Programming, Mixed-Integer Programming | https://www.gurobi.com/ | Mathematics | https://www.gurobi.com/documentation/current/examples/index.html https://support.gurobi.com/hc/en-us/articles/13444017491857-How-do-I-use-the-Gurobi-Command-Line-Interface-gurobi-cl https://support.gurobi.com/hc/en-us/articles/14165975461393-Tutorials-Getting-Started-with-the-Gurobi-APIs |
Anvil: https://www.rcac.purdue.edu/software/gurobi Bridges-2: https://www.psc.edu/resources/software/gurobi Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html |
Anvil: 9.5.1 Bridges-2: 9.1.1, 9.5.0 Delta: 10.0.1 |
Optimization Software | |||
gurobi-dev | Delta | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 10.0.3 | |||||||||||||
gymnasium | Faster | Gymnasium is a Python library which provides tools and utilities for creating and manipulating complex mathematical expressions and equations. | 1. Allows users to create and manipulate mathematical expressions\r 2. Supports complex mathematical operations and transformations\r 3. Provides a simple and intuitive interface for working with mathematical equations\r 4. Compatible with Python programming language\r 5. Useful for symbolic mathematics and equation handling tasks |
Programming Library | Applied Computer Science | Computer Science | Python Library, Mathematical Expressions, Equation Manipulation | Mathematics | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.26.3 | Library | |||||
gzip | Aces, Faster | gzip is a single-file/stream lossless data compression utility, where the resulting compressed file generally has the suffix .gz. gzip also refers to the associated compressed data format used by the utility. Description Source: https://www.gzip.org/ |
gzip is a file compression and decompression tool used to reduce the size of files for storage or transfer purposes. It is a widely used compression utility in Unix-like operating systems. | Compression and decompression of files, support for various compression levels, integration with tar for creating compressed archives, fast and efficient compression algorithms. | https://www.gnu.org/software/gzip/manual/gzip.html | Compression Tool | File Compression, Data Storage, Data Transfer | https://www.gnu.org/software/gzip/ | Engineering & Technology | https://www.gnu.org/software/gzip/manual/gzip.html#Sample https://www.gnu.org/software/gzip/manual/gzip.html#Invoking-gzip https://www.youtube.com/watch?v=NLtt4S9ErIA |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.10, 1.12 Faster: 1.10, 1.12 |
Utility | |||
h5py | Aces, Faster | The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. Description Source: https://www.h5py.org/ |
h5py is a Python library providing a high-level interface to the HDF5 library. It allows you to store huge amounts of numerical data and easily manipulate that data from NumPy. | High-Level Interface To The Hdf5 Library, Efficiently Store & Manipulate Large Numerical Datasets, Seamless Integration With Numpy Arrays, Support For Complex Data Structures, Ability To Access Data Stored In Hdf5 Files | https://docs.h5py.org/en/stable/ | Library | Python Library, Data Storage, Numerical Data, Data Manipulation | https://www.h5py.org/ | Computer & Information Sciences | https://docs.h5py.org/en/stable/quick.html#core-concepts https://docs.h5py.org/en/stable/high/file.html#opening-creating-files |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.1.0, 3.2.1, 3.6.0, 3.7.0, 3.8.0, 3.9.0, 3.10.0 Faster: 2.10.0-Python-3.7.4, 2.10.0-Python-3.8.2, 3.1.0, 3.2.1, 3.6.0, 3.7.0, 3.8.0 |
Python Library | |||
hadoop | Anvil, Expanse | The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. Description Source: https://hadoop.apache.org/ |
Hadoop is an open-source framework used for distributed storage and processing of large sets of data on computer clusters using simple programming models. | Distributed Storage, Distributed Processing, Fault Tolerance, Scalability, Flexibility, High Availability | https://apache.github.io/hadoop/ | Framework | Big Data, Data Processing, Distributed Computing | https://hadoop.apache.org/ | Computer & Information Sciences | https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-common/UnixShellGuide.html https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html https://www.tutorialspoint.com/hadoop/index.htm |
Anvil: https://www.rcac.purdue.edu/software/hadoop Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 3.3.0 Expanse: Bfyu354 |
Data Processing | |||
hail | Anvil | Hail is an open-source, general-purpose, Python-based data analysis tool with additional data types and methods for working with genomic data. | Hail is an open-source, scalable genetic analysis platform built to store and process large-scale genetic data with ease. It is tailored for exploring, analyzing, and visualizing genomic data on research scale. | Scalable Genetic Analysis Platform, Storage & Processing Of Large-Scale Genetic Data, Exploration, Analysis, & Visualization Of Genomic Data, Support For High-Throughput Sequencing Data, Integration With Apache Spark For Distributed Computing | Analysis Tool | Genetic Analysis, Genomics, Big Data, Bioinformatics, Genetic Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/hail | Anvil: 0.2.94, 0.2.98 | Bioinformatics & Computational Biology | ||||||
hap.py | Anvil | Hap.py is a tool to compare diploid genotypes at haplotype level. | hap.py is a toolkit for assessing the accuracy of variants (SNPs, indels, and block substitutions) detected by various sequencing technologies, including data from whole-genome sequencing, whole-exome sequencing, and targeted gene panels. | It provides a variety of metrics for evaluating variant calls, such as precision, recall, F1 score, sensitivity, specificity, and more. It supports VCF and BED files as input and generates detailed reports to aid in interpreting the accuracy of variant calls. | Bioinformatics Tool | Variant Calling, Sequencing, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/hap.py | Anvil: 0.3.9 | Computational Tool | ||||||
harfbuzz | Aces, Faster, Ookami | HarfBuzz is a text shaping library. Using the HarfBuzz library allows programs to convert a sequence of Unicode input into properly formatted and positioned glyph output—for any writing system and language. Description Source: https://harfbuzz.github.io/ |
HarfBuzz is an open-source text shaping engine. It is used to convert Unicode text to beautifully formatted and language-appropriate glyphs. HarfBuzz focuses on providing correct script shaping for complex scripts and languages. | Unicode text shaping, support for complex scripts, language-specific shaping rules, high-quality text layout, customization options for font features, text rendering optimization. | https://harfbuzz.github.io/ | Library | Text Shaping Engine, Unicode Text, Text Layout, Font Features Customization | https://github.com/harfbuzz/harfbuzz | Computer & Information Sciences | https://harfbuzz.github.io/getting-started.html https://harfbuzz.github.io/a-simple-shaping-example.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 2.8.1, 2.8.2, 4.2.1, 5.3.1 Faster: 2.6.4, 2.6.7, 2.8.1, 2.8.2, 4.2.1, 5.3.1 Ookami: 8.3.0 |
Package | |||
hashdeep | Bridges-2 | hashdeep is a program to compute, match, and audit hashsets. With traditional matching, programs report if an input file matched one in a set of knows or if the input file did not match. It's hard to get a complete sense of the state of the input files compared to the set of knowns. It's possible to have matched files, missing files, files that have moved in the set, and to find new files not in the set. Hashdeep can report all of these conditions. It can even spot hash collisions, when an input file matches a known file in one hash algorithm but not in others. The results are displayed in an audit report. Description Source: https://md5deep.sourceforge.net/ |
hashdeep is a cross-platform hashing utility that calculates and verifies hash signatures for files and directories. | The tool supports multiple hashing algorithms such as MD5, SHA-1, SHA-256, SHA-384, SHA-512, and many others. It can recursively compute hashes for files in a directory structure, output the results in various formats, and verify file integrity by comparing hashes. | https://md5deep.sourceforge.net/hashdeep.html | Hashing | Hashing, Data Integrity, Security | https://github.com/jessek/hashdeep | Computer & Information Sciences | https://md5deep.sourceforge.net/start-hashdeep.html https://github.com/jessek/hashdeep/blob/master/doc/start-hashdeep.html |
Bridges-2: https://www.psc.edu/resources/software/hashdeep | Bridges-2: 4.4 | Utility | |||
hatchling | Aces, Faster | Extensible, standards compliant build backend used by Hatch, a modern, extensible Python project manager. | Hatchling is a software tool designed for simulating and analyzing population dynamics in ecological studies, particularly focusing on early life stages of organisms such as fish, amphibians, and invertebrates. It allows researchers to model various environmental factors affecting the survival and growth of hatchlings in different ecosystems. | Population Dynamics Modeling, Simulation Of Early Life Stages Of Organisms, Analysis Of Environmental Factors On Hatchling Survival & Growth, Ecological Study Support | Research Tool | Population Dynamics Of Early Life Stages | Environmental Biology | Population Dynamics, Ecology, Simulation, Environmental Factors | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.18.0 Faster: 1.11.1, 1.18.0 |
Simulation & Modeling | ||||
hdbscan | Faster | HDBSCAN (Hierarchical Density-Based Spatial Clustering of Applications with Noise) is a clustering algorithm that is based on density rather than distance, and in contrast to many other clustering algorithms, HDBSCAN has a parameterless approach that automatically determines the number of clusters in the data. | Density-Based Clustering, Automatic Cluster Determination, Ability To Handle Noise/Outliers, Scalable To Large Datasets, Robust To Different Cluster Geometries & Densities | Data Mining Tool | Clustering Algorithm, Data Mining, Unsupervised Learning, Machine Learning | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.8.27 | Clustering Algorithm | |||||||
hdf | Aces, Anvil, Expanse, Faster | Hierarchical Data Format (HDF) refers to a versatile file format commonly used to store and manage large volumes of complex data, such as scientific datasets and images. It provides a standardized and efficient way for organizing and sharing data. | HDF (Hierarchical Data Format) is a flexible and extensible file format for storing and managing large amounts of data. It supports various data types, attributes, and metadata, making it suitable for a wide range of scientific and engineering applications. | Supports Large, Complex, & Multidimensional Datasets, Allows For Efficient Data Organization & Storage, Provides Tools For Data Management, Manipulation, & Visualization, Offers Apis For Different Programming Languages Such As C, Python, & Java | https://portal.hdfgroup.org/documentation/hdf4-docs/HDF4_Reference_Manual.pdf | File Format | Data Management, File Format, Data Visualization, Api | https://portal.hdfgroup.org/hdf4/ | Other Computer & Information Sciences | https://portal.hdfgroup.org/documentation/hdf4-docs/HDF4_Users_Guide.pdf | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/hdf Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 4.2.15, 4.2.16-2 Anvil: 4.2.15 Expanse: 4.2.15 Faster: 4.2.15, 4.2.16-2 |
Data Management & Storage | |||
hdf-eos | Aces | HDF-EOS libraries are software libraries built on HDF libraries. It supports three data structures for remote sensing data: Grid, Point and Swath. | HDF-EOS (Hierarchical Data Format - Earth Observing System) is a software library developed by NASA for managing and processing Earth science data in the HDF (Hierarchical Data Format) format. | 1. Provides tools for managing and processing Earth science data.\r 2. Supports a wide range of data formats and metadata.\r 3. Includes libraries for data visualization, extraction, and manipulation.\r 4. Optimized for handling large volumes of geospatial data.\r 5. Designed specifically for the storage and retrieval of Earth science data. |
Library | Atmospheric Sciences | Earth & Environmental Sciences | Data Management, Data Processing, Earth Science, Geospatial Data | Physical Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 2.20 | Computational Software | ||||
hdf-eos5 | Aces | HDF-EOS libraries are software libraries built on HDF libraries. It supports three data structures for remote sensing data: Grid, Point and Swath. | HDF-EOS5 is a software library developed by NASA that provides tools and interfaces for working with EOS (Earth Observing System) data in the Hierarchical Data Format (HDF5) format. It is specifically designed for the management and analysis of Earth science data collected by various NASA missions. | 1. Tools for reading, writing, and manipulating HDF5 files\r 2. Support for EOS data structures and metadata\r 3. APIs for accessing and processing EOS datasets\r 4. Integration with popular programming languages like C, Fortran, and Python\r 5. Visualization capabilities for Earth science data |
Data Management & Analysis | Atmospheric Sciences | Earth & Environmental Sciences | Nasa, Earth Observing System, Data Management, Data Analysis, Hdf5 Format | Natural Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.16 | Library | ||||
hdf4 | Darwin | Hierarchical Data Format Version 4 (HDF4) is a data management software library and file format that provides high-performance I/O capabilities for storing and managing large and complex data. HDF4 is designed to support diverse data types and structures, enabling efficient data storage, retrieval, and sharing. | 1. Support for various data types and structures\r 2. High-performance I/O operations\r 3. Scalable and flexible data storage\r 4. Tools for data visualization and manipulation\r 5. Support for parallel and distributed computing\r 6. Cross-platform compatibility |
Library | Data Management, I/O Operations, Data Storage, Data Visualization, Parallel Computing | Computer & Information Sciences | Data Management | |||||||||
hdf5 | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Ookami, Stampede3 | HDF5 is a data model, library, and file format for storing and managing data. It supports an unlimited variety of datatypes, and is designed for flexible and efficient I/O and for high volume and complex data | HDF5 (Hierarchical Data Format version 5) is a file format and a suite of tools developed by the HDF Group for managing and storing large and complex data. It is designed to store and organize large amounts of data efficiently, enabling fast data access and sharing. | Support For Various Data Types & Structures, Hierarchical Organization Of Data, High-Performance I/O Capabilities, Parallel I/O For Large-Scale Data Processing, Data Compression & Chunking For Efficient Storage, Cross-Platform Compatibility, Support For Metadata & Attributes, Integration With Other Programming Languages Like Python, C, & Fortran | https://docs.hdfgroup.org/hdf5/develop/ | Library/Tool | File Format, Data Management, Data Storage, Data Sharing, High-Performance Computing | https://www.hdfgroup.org/solutions/hdf5/ | Other Computer & Information Sciences | https://docs.hdfgroup.org/hdf5/develop/_getting_started.html https://docs.hdfgroup.org/hdf5/develop/_u_g.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/hdf5 Bridges-2: https://www.psc.edu/resources/software/hdf5 Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 1.10.7, 1.12.1, 1.12.2, 1.14.0, 1.14.2, 1.14.3 Anvil: 1.10.7 Bridges-2: 1.10.7-Gcc10.2.0, 1.12.0-Intel20.4 Delta: 1.14.3 Expanse: Butdr5C, E27Q55Q, ... Faster: 1.10.2, 1.10.5, 1.10.6, 1.10.7, 1.12.1, 1.12.2, 1.13.1, 1.14.0, 1.14.3 Ookami: Parallel/Openmpi/Llvm14/1.12.1 Stampede-3: 1.10.11, 1.14.0, 1.14.3 |
Data Management | |||
helen | Anvil | HELEN is a multi-task RNN polisher which operates on images produced by MarginPolish. | Helen is a software tool for analyzing genomic and epigenomic annotations from large-scale sequencing data. It is designed to extract biological insights from high-throughput sequencing data related to DNA modifications and chromatin structure. | Helen offers various features including the ability to perform differential analysis of epigenetic marks, identify enriched regions of histone modifications, visualize genomic annotations, and integrate multiple types of epigenomic data for comprehensive analysis. | Tools | Genetics | Biophysics | Genomic Analysis, Epigenomics, High-Throughput Sequencing, DNA Modifications, Chromatin Structure | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/helen | Anvil: 1.0 | Bioinformatics | ||||
help2man | Aces, Faster | help2man is a tool for automatically generating simple manual pages from program output. Description Source: https://www.gnu.org/software/help2man/#Overview |
help2man is a tool that can generate simple man pages from the '--help' and '--version' output of other commands. | help2man automates the generation of manual pages for programs that lack a man page but provide a '--help' or '--version' option. It extracts the necessary information from these options and formats them into a manual page. | https://www.gnu.org/software/help2man/ | Utility | Software Development | Software Engineering, Systems, & Development | Documentation, Man Pages, Automation | https://www.gnu.org/software/help2man/ | Engineering & Technology | https://www.gnu.org/software/help2man/help2man.html#Example | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.47.8, 1.47.16, 1.48.3, 1.49.2, 1.49.3 Faster: 1.47.4, 1.47.7, 1.47.8, 1.47.10, 1.47.12, 1.47.16, 1.48.3, 1.49.2, 1.49.3 |
Documentation Tool | |
hh-suite | Aces, Faster | HH-suite is a widely used open source software suite for sensitive sequence similarity searches and protein fold recognition. It is based on pairwise alignment of profile Hidden Markov models (HMMs), which represent multiple sequence alignments of homologous proteins. Description Source: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3019-7 |
HH-suite is a software package for sensitive protein sequence searching based on profile hidden Markov models. It includes tools for the alignment of protein sequences, detecting remote homologs, and predicting protein structures. | 1. Sensitive protein sequence searching using profile hidden Markov models. 2. Alignment of protein sequences. 3. Detection of remote homologs. 4. Prediction of protein structures. | https://github.com/soedinglab/hh-suite/wiki#summary-of-command-line-parameters | Computational Software | Protein Sequence Searching, Profile Hidden Markov Models, Protein Structure Prediction | https://github.com/soedinglab/hh-suite | Biological Sciences | https://github.com/soedinglab/hh-suite/wiki#brief-tutorial-to-hhsuite-tools | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.3.0 Faster: 3.3.0 |
Bioinformatics | |||
hic-pro | Anvil | Hicpro is an optimized and flexible pipeline for Hi-C data processing. | HiC-Pro is a bioinformatics pipeline for processing, analyzing, and visualizing high-throughput chromatin conformation capture (Hi-C) data. It allows users to generate significant biological insights by studying chromatin structure, genome organization, and 3D chromatin interactions. | Preprocessing Raw Hi-C Data, Mapping Reads To The Reference Genome, Filtering & Processing Valid Interaction Pairs, Normalization & Visualization Of Interactions, Quality Control Assessment Of Hi-C Data, Identifying Topological Domains & Chromatin Interactions | Data Analysis | Chromatin Structure & Function | Genomics | Bioinformatics, Genomics, Chromatin Structure, Hi-C Data, Data Visualization, Chromatin Interactions | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/hic-pro | Anvil: 3.0.0, 3.1.0 | Bioinformatics Tool | ||||
hicexplorer | Anvil | Hicexplorer is a set of tools to process, normalize and visualize Hi-C data. | HicExplorer is a software package designed for the analysis, visualization, and interpretation of Hi-C data, which is used to study the 3D organization of the genome. | Processing & Normalization Of Hi-C Data, Identification Of Topologically Associated Domains (Tads), Visualization Of Hi-C Contact Matrices, Detection Of Chromatin Loops, Analysis Of Interaction Frequencies Between Genomic Regions | Bioinformatics | Chromatin Structure | Genomics | Hi-C Data Analysis, Genome 3D Organization, Genomics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/hicexplorer | Anvil: 3.7.2 | Data Analysis | ||||
hifiasm | Anvil, Faster | Hifiasm is fast haplotype-resolved de novo assembler for PacBio HiFi reads. | Hifiasm is a fast and scalable haplotype-resolved de novo assembler for PacBio HiFi reads. | Haplotype-Resolved De Novo Assembly, Supports Pacbio Hifi Reads, Fast & Scalable | Bioinformatics | Genetics | Biological Sciences | Assembler, De Novo Assembly | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/hifiasm Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 0.16.0, 0.18.5 Faster: 0.19.4-R575 |
Genome Assembly | ||||
highway | Aces, Faster | Highway is a C++ library that provides portable SIMD/vector intrinsics. Description Source: https://github.com/google/highway |
HighWay is an open-source statistical software tool designed for the identification of driver genes and pathways in cancer based on the analysis of somatic mutations across a cohort of tumor samples. | Identification Of Driver Genes & Pathways In Cancer, Analysis Of Somatic Mutations, Processing Of Tumor Samples | https://google.github.io/highway/en/master/ | Statistical Tool | Genetics | Bioinformatics | Bioinformatics, Computational Biology, Statistical Analysis | https://github.com/google/highway | Biological Sciences | https://google.github.io/highway/en/master/README.html#examples https://google.github.io/highway/en/master/README.html#quick-start |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.0.3, 1.0.4 Faster: 1.0.3, 1.0.4 |
Data Analysis | |
hipify-clang | Faster | hipify-clang is a tool that translates CUDA code to HIP (Heterogeneous-Compute Interface for Portability) code, enabling the porting of CUDA applications to AMD GPUs. | 1. Translates CUDA source code to HIP source code.\r 2. Facilitates the migration of CUDA applications to AMD GPUs.\r 3. Helps in leveraging the performance of AMD GPUs for existing CUDA projects. |
Code Translation Tool | Cuda, Hip, Gpu Computing, Code Translation | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 4.2.0 | Compiler | |||||||
hipsycl | Faster | hipsycl is a SYCL implementation targeting CPUs, CUDA, and HIP backends for heterogeneous systems, allowing for portable performance across different hardware platforms. | 1. Support for SYCL, a single-source standard for heterogeneous parallel programming. 2. Targeting CPUs, CUDA, and HIP backends for flexibility in hardware support. 3. Portable performance across different hardware platforms. 4. Integration with various development environments and tools for ease of use. | Programming Library | Parallel & Distributed Computing | Computer Science | Heterogeneous Computing, Parallel Programming, Hardware Acceleration | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 0.9.3 | Compiler | |||||
hiredis | Aces, Faster | Hiredis is a minimalistic C client library for the Redis database. Description Source: https://github.com/redis/hiredis |
Hiredis is a minimalistic C client library for the Redis database, offering a simple interface to interact with Redis servers from C-based applications. It aims to maintain an API that is both high-performance and easy to use, providing basic functionality to communicate with Redis servers. | 1. Support for connecting to Redis servers\r 2. Commands to execute Redis commands like SET, GET, INCR, etc.\r 3. Asynchronous operation support\r 4. Pipelining support for performing multiple commands in a single round trip |
https://github.com/redis/hiredis | Library | Redis, Database, C Library | https://redis.io/lp/hiredis/ | Computer & Information Sciences | https://github.com/redis/hiredis/blob/master/examples/example.c https://github.com/redis/hiredis/tree/master/examples |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.0.2 Faster: 1.0.2 |
Client Library | |||
hisat2 | Aces, Anvil, Bridges-2, Expanse, Faster | HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes as well as to a single reference genome. Based on an extension of BWT for graphs (Sirén et al. 2014), we designed and implemented a graph FM index (GFM), an original approach and its first implementation. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome. These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM). Description Source: https://daehwankimlab.github.io/hisat2/ |
HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) against the general human population (as well as against a single reference genome). It builds on HISAT and Bowtie, allowing for significantly improved performance and new capabilities. | Fast & Sensitive Alignment Of Ngs Reads, Mapping Of DNA & RNA Reads, Alignment Against General Human Population Or A Single Reference Genome, Improved Performance & New Capabilities Compared To Hisat & Bowtie | https://daehwankimlab.github.io/hisat2/manual/ | Alignment Tool | Sciences | Biology | Alignment, Ngs, Genomics, Transcriptomics | https://daehwankimlab.github.io/hisat2/ | Biological Sciences | https://daehwankimlab.github.io/hisat2/howto/ . https://daehwankimlab.github.io/hisat2/manual/#getting-started-with-hisat2 https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/rna-seq-reads-to-counts/tutorial.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/hisat2 Bridges-2: https://www.psc.edu/resources/software/hisat2 Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.2.1 Anvil: 2.2.1 Bridges-2: 2.2.1 Expanse: Qip6Jby Faster: 2.2.1 |
Bioinformatics | |
hmmer | Aces, Anvil, Bridges-2, Faster | HMMER is used for searching sequence databases for sequence homologs, and for making sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs). Description Source: http://hmmer.org/ |
Hmmer is a software suite used for protein sequence analysis based on profile hidden Markov models (HMMs). It is widely used for searching sequence databases for homologs of protein sequences, identifying conserved protein domains, and annotating protein sequences based on sequence alignment. | Protein Sequence Analysis, Profile Hidden Markov Models (Hmms), Homology Search, Conserved Protein Domain Identification, Sequence Annotation | http://hmmer.org/documentation.html | Bioinformatics Tool | Proteomics | Bioinformatics | Bioinformatics, Computational Biology, Proteomics, Sequence Analysis | http://hmmer.org/ | Biological Sciences | http://eddylab.org/software/hmmer/Userguide.pdf https://github.com/EddyRivasLab/hmmer/blob/master/documentation/userguide/tutorial.tex |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/hmmer Bridges-2: https://www.psc.edu/resources/software/hmmer Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.3.2 Anvil: 3.3.2 Bridges-2: 3.3.1 Faster: 3.3.2 |
Analysis Tool | |
homer | Anvil, Bridges-2 | HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. Description Source: http://homer.ucsd.edu/homer/motif/ |
HOMER (Hypergeometric Optimization of Motif EnRichment) is a suite of tools for motif discovery and next-gen sequencing analysis. It is widely used for identifying transcription factor binding sites and novel motifs in DNA sequences. | 1. Motif discovery in DNA sequences. 2. Identification of transcription factor binding sites. 3. Next-generation sequencing data analysis. 4. De novo motif discovery. 5. Integration with various genomic databases. | http://homer.ucsd.edu/homer/introduction/programs.html | Tool | Bioinformatics | Genetics | Bioinformatics, Next-Generation Sequencing, Motif Discovery, Transcription Factor Binding Sites | http://homer.ucsd.edu/homer/ | Biological Sciences | http://homer.ucsd.edu/homer/basicTutorial/index.html http://homer.ucsd.edu/homer/motif/index.html |
Anvil: https://www.rcac.purdue.edu/software/homer Bridges-2: https://www.psc.edu/resources/software/homer |
Anvil: 4.11 Bridges-2: 4.11.0 |
Computational Biology | |
homopolish | Anvil | Homopolish is a genome polisher originally developed for Nanopore and subsequently extended for PacBio CLR. | Homopolish is a tool for polishing long-read assemblies using shorter reads. It takes long reads from a genome assembly and error-corrects them using short reads to produce a more accurate assembly. | Error Correction Of Long-Read Assemblies Using Short Reads, Improving The Accuracy Of Genome Assemblies, Facilitates The Generation Of High-Quality Genome Assemblies | Genome Assembly Tool | Genomics | Bioinformatics | Bioinformatics, Genome Assembly, Error Correction, Long Reads, Short Reads | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/homopolish | Anvil: 0.4.1 | Bioinformatics Tool | ||||
horovod | Aces, Faster | Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. Description Source: https://horovod.ai/ |
Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and MXNet. It significantly improves the speed and scale of distributed deep learning training. | Horovod supports training deep learning models on multiple GPUs across multiple nodes, providing fast and efficient distributed training. It is designed to be easy to use and integrates seamlessly with popular deep learning frameworks such as TensorFlow, Keras, PyTorch, and MXNet. Horovod incorporates optimizations for reducing communication overhead and achieving high performance on large-scale distributed systems. | https://horovod.readthedocs.io/en/stable/ | Library/Framework | Deep Learning, Distributed Training, Machine Learning, Gpu Acceleration, High Performance Computing | https://horovod.ai/ | Computer & Information Sciences | https://horovod.ai/getting-started/ https://horovod.readthedocs.io/en/stable/summary_include.html#usage https://horovod.readthedocs.io/en/stable/summary_include.html#guides |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.22.1-Cuda-11.3.1-Tensorflow-2.6.0, 0.28.1-Cuda-11.7.0-Tensorflow-2.11.0, 0.28.1-Cuda-11.7.0-Pytorch-1.12.1 Faster: 0.18.2-Tensorflow-1.15.2-Python-3.7.4, 0.22.0-Pytorch-1.8.1, 0.22.1-Cuda-11.3.1-Tensorflow-2.6.0, 0.23.0-Tensorflow-2.5.0, ... |
Distributed Deep Learning Training Framework | |||
hossedu | Faster | HOSSedu is an educational software tool designed for teaching and learning in the field of computer science and programming. | This software provides interactive lessons, coding exercises, quizzes, and tutorials to help students understand concepts such as data structures, algorithms, programming languages, and software development. | Teaching & Learning Tool | Computer Science | Educational Software, Computer Science, Programming | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2018 | Educational Software | ||||||
how_are_we_stranded_here | Anvil | How_are_we_stranded_here is a python package for testing strandedness of RNA-Seq fastq files. | Anvil: https://www.rcac.purdue.edu/software/how_are_we_stranded_here | Anvil: 1.0.1 | ||||||||||||
hpc toolkit | Jetstream | HPCToolkit is an integrated suite of tools for measurement and analysis of program performance on computers ranging from multicore desktop systems to the nation's largest supercomputers. By using statistical sampling of timers and hardware performance counters, HPCToolkit collects accurate measurements of a program's work, resource consumption, and inefficiency and attributes them to the full calling context in which they occur. Description Source: http://hpctoolkit.org/ |
HPC Toolkit is a collection of tools designed to assist users in optimizing and analyzing the performance of their parallel scientific applications on high-performance computing (HPC) systems. | Performance Analysis, Debugging Support, Profiling Capabilities, Parallel Code Optimization, Visualization Of Performance Data | http://hpctoolkit.org/documentation.html | Toolkit | Hpc, Performance Analysis, Parallel Computing, Optimization, Debugging | http://hpctoolkit.org/ | Engineering & Technology | http://hpctoolkit.org/manual/HPCToolkit-users-manual.pdf http://hpctoolkit.org/training.html |
Performance Analysis Tools | |||||
hpc-x | Aces | NVIDIA HPC-X is a comprehensive software package that includes Message Passing Interface (MPI), Symmetrical Hierarchical Memory (SHMEM) and Partitioned Global Address Space (PGAS) communications libraries, and various acceleration packages. | hpc-x is a high-performance computing (HPC) software package designed to provide optimized libraries, tools, and compilers for scientific computing on HPC systems. It aims to enhance the performance and efficiency of parallel computing applications on modern HPC architectures. | hpc-x includes optimized libraries and tools for parallel computing, high-performance compilers, performance analysis tools, and debugging utilities. It provides support for distributed memory parallel computing using MPI (Message Passing Interface) and shared memory parallel computing using OpenMP. | Hpc Tools | Hpc, High-Performance Computing, Scientific Computing, Parallel Computing | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 2.14 | Tools & Libraries | ||||||
hpctoolkit | Anvil | HPCToolkit is an integrated suite of tools for measurement and analysis of program performance on computers ranging from multicore desktop systems to the nation's largest supercomputers. By using statistical sampling of timers and hardware performance counters, HPCToolkit collects accurate measurements of a program's work, resource consumption, and inefficiency and attributes them to the full calling context in which they occur. Description Source: http://hpctoolkit.org/ |
http://hpctoolkit.org/documentation.html | http://www.hpctoolkit.org/ | http://hpctoolkit.org/manual/HPCToolkit-users-manual.pdf http://hpctoolkit.org/training.html |
Anvil: https://www.rcac.purdue.edu/software/hpctoolkit | Anvil: 2021.03.01 | |||||||||
hpcx | Darwin | HPCx is a high-performance computing environment developed for scientific and engineering applications. It provides a platform for researchers to perform complex simulations and data analysis tasks efficiently. | High-Performance Computing, Scientific & Engineering Applications Support, Efficient Simulations, Data Analysis Capabilities | Computational Software | High-Performance Computing, Scientific Computing, Data Analysis | Engineering & Technology | Hpc Tools | |||||||||
hpl | Expanse, Faster | The High Performance Linpack (HPL) benchmark is a tool for analyzing and ranking the performance of computer systems, particularly supercomputers. It measures the floating-point rate of execution for solving a dense system of linear equations. HPL is widely used to assess and compare the computational performance of High Performance Computing (HPC) systems. | Measures The Floating-Point Rate Of Execution For Solving Linear Equations, Provides A Standardized Benchmark For Comparing Hpc Systems, Used To Assess & Rank The Performance Of Supercomputers | Benchmarking Tool | Performance Evaluation & Benchmarking | Infrastructure & Instrumentation | Hpc, Benchmarking, Performance Analysis | Engineering & Technology | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Expanse: Bok66Cm, De4T44F-Omp, Iyq74Za, ... Faster: 2.3 |
Computational Software | |||||
hprc_utils | Aces | HPRC_utils is a collection of useful utilities to accompany software modules on the TAMU HPRC clusters. | hprc_utils is a collection of utility tools for managing and analyzing High Performance Computing (HPC) environments and workflows. | Some of the core features of hprc_utils include job submission, monitoring, resource management, data transfer, job scheduling, workflow optimization, and HPC environment setup. | Tool | Hpc, High Performance Computing, Utility Tools | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.0 | Utility | ||||||
htop | Delta, Faster, Ookami | This is htop, a cross-platform interactive process viewer. It is a text-mode application (for console or X terminals) and requires ncurses. Description Source: https://htop.dev/ |
htop is an interactive system-monitor process-viewer for Unix systems. It provides a detailed overview of system performance and resource usage in a visually appealing and user-friendly interface. | Real-Time Monitoring Of System Processes, Interactive Process Viewer With Easy Navigation, Color-Coded Display For Cpu, Memory, & Swap Usage, Ability To Search For Processes & Filter Based On Various Criteria, Customizable Display Options & Settings, Support For Mouse Interaction | https://linux.die.net/man/1/htop | Monitoring Tool | System Monitoring, Process Viewer, Resource Usage | https://htop.dev/ | Engineering & Technology | https://www.tecmint.com/htop-linux-process-monitoring/ https://www.geeksforgeeks.org/using-htop-to-monitor-system-processes-on-linux/ |
Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Delta: 3.2.2 Faster: 2.0.0, 2.0.1, 3.0.5 Ookami: 3.2.1 |
System Tool | |||
htseq | Aces, Anvil, Faster | HTSeq is a Python library to facilitate processing and analysis of data from high-throughput sequencing (HTS) experiments. | HTSeq is a Python library that provides efficient tools to work with high-throughput sequencing data. It offers functionalities to process and analyze sequence data from RNA-Seq experiments, particularly for quantification of gene and transcript expression levels. | Quantification Of Gene Expression Levels, Handling High-Throughput Sequencing Data, RNA-Seq Data Analysis, Python Library For Bioinformatics | Bioinformatics Tool | Transcriptomics | Bioinformatics | Bioinformatics, RNA-Seq, High-Throughput Sequencing, Gene Expression, Sequence Data | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/htseq Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.0.2 Anvil: 0.11.2, 0.13.5, 1.99.2, 2.0.1, 2.0.2-Py310, 2.0.2 Faster: 2.0.2 |
Python Library | ||||
htslib | Aces, Anvil, Bridges-2, Expanse, Faster | HTSlib is an implementation of a unified C library for accessing common file formats, such as SAM, CRAM and VCF, used for high-throughput sequencing data, and is the core library used by samtools and bcftools. HTSlib only depends on zlib. It is known to be compatible with gcc, g++ and clang. Description Source: https://github.com/samtools/htslib |
HTSlib is a C library for processing high-throughput sequencing data in the form of SAM, BAM, and CRAM formats. It allows for efficient reading, writing, and manipulation of such files, as well as various operations such as format conversion, indexing, and retrieval of specific sequences. | Support For Sam, Bam, & Cram Formats, Efficient Reading & Writing Of Sequencing Data Files, File Format Conversion & Manipulation, Indexing & Retrieval Of Sequences, Integration With Other Bioinformatics Tools | https://www.htslib.org/doc/ | Data Processing | Next-Generation Sequencing | Genomics | Bioinformatics, Sequencing Data, File Format Processing, C Library | https://www.htslib.org/ | Biological Sciences | https://github.com/samtools/htslib/blob/develop/htslib/hts.h https://www.htslib.org/howtos/headers.html |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/htslib Bridges-2: https://www.psc.edu/resources/software/htslib Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.15.1 Anvil: 1.14, 1.15, 1.16, 1.17 Bridges-2: 1.13 Expanse: 4Yylg6I Faster: 1.10.2, 1.12, 1.14, 1.15.1, 1.17 |
Library | |
htstream | Anvil | Htstream is a quality control and processing pipeline for High Throughput Sequencing data. | htstream is a software package that provides scalable, high-throughput tools for processing short-read sequencing data. It is designed to efficiently handle large-scale genomic datasets and perform various data processing tasks for bioinformatics applications. | Key features of htstream include fast and parallel processing of short-read sequencing data, quality control and filtering of reads, mapping reads to reference genomes, generating alignment statistics, and facilitating downstream analysis such as variant calling and differential expression analysis. | Data Processing Tool | Genetics | Biological Sciences | Bioinformatics, Sequencing Data, Data Processing | Natural Sciences | Anvil: https://www.rcac.purdue.edu/software/htstream | Anvil: 1.3.3 | Computational Tool | ||||
https | Faster | Faster: https://hprc.tamu.edu/software/faster/ | ||||||||||||||
humann | Aces, Anvil | Humann is a pipeline for efficiently and accurately profiling the presence/absence and abundance of microbial pathways in a community from metagenomic or metatranscriptomic sequencing data (typically millions of short DNA/RNA reads). | HUMAnN (HMP Unified Metabolic Analysis Network) is a tool for efficiently and accurately profiling the presence and abundance of microbial pathways in a community from metagenomic shotgun sequencing data. It combines sequence alignment and gene activity profiling to quantify the presence of pathway modules. | 1. Pathway abundance profiling from metagenomic sequencing data\r 2. Integration of sequence alignment and gene activity profiling\r 3. Quantification of microbial pathways in a community\r 4. Visualization tools for pathway analyses |
Analysis Tool | Ecology | Biological Sciences | Metagenomics, Microbiome, Pathway Analysis, Bioinformatics | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/humann |
Aces: 3.6 Anvil: 3.0.0, 3.6 |
Bioinformatics | ||||
hunspell | Aces, Faster | Hunspell is a spell checker and morphological analyzer library and program designed for languageswith rich morphology and complex word compounding or character encoding. | Hunspell is a spell checker and morphological analyzer software designed for languages with rich morphology and complex word compounding. | 1. Spell checking and suggestion capabilities. 2. Morphological analysis for complex languages. 3. Support for hyphenation, Thesaurus, and morphological generation. 4. Cross-platform compatibility. 5. Customizable and extensible dictionaries. | Utility | Spell Checker, Morphological Analyzer, Language Support | Other Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.7.1 Faster: 1.7.1 |
Spell Checking & Morphological Analysis Software | ||||||
hwloc | Aces, Anvil, Darwin, Delta, Expanse, Faster, Kyric, Ookami | The Portable Hardware Locality (hwloc) software package provides a portable abstraction (across OS, versions, architectures, ...) of the hierarchical topology of modern architectures, including NUMA memory nodes (DRAM, HBM, non-volatile memory, CXL, etc.), sockets, shared caches, cores and simultaneous multithreading. It also gathers various system attributes such as cache and memory information as well as the locality of I/O devices such as network interfaces, InfiniBand HCAs or GPUs. Description Source: https://www.open-mpi.org/projects/hwloc/ |
hwloc, the Portable Hardware Locality (hwloc), is an open-source hierarchical machine topology library used to provide abstract representation of the hierarchical topology of modern architectures. | Some core features of hwloc include the ability to identify the hierarchy of processing units, caches, memory, and locality information, support for a variety of hardware and software platforms, APIs for querying and modifying the topology, support for NUMA (Non-Uniform Memory Access) and processor binding policies, and visualization tools. | https://www.open-mpi.org/projects/hwloc/doc/v2.10.0/ | Library | System Software | Computer Science | Machine Topology, Hardware Architecture, System Software | https://www.open-mpi.org/projects/hwloc/ | Computer & Information Sciences | https://www.open-mpi.org/projects/hwloc/tutorials/ | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/hwloc Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 2.2.0, 2.4.1, 2.5.0, 2.7.1, 2.8.0, 2.9.1, 2.9.2 Anvil: 1.11.13 Delta: 2.2.0 Expanse: 1.11.11, 2.2.0 Faster: 1.11.10, 1.11.12, 2.2.0, 2.4.1, 2.5.0, 2.7.1, 2.8.0, 2.9.1, 2.9.2 Kyric: 2.1.0 Ookami: 2.8.0 |
Library | |
hyper-shell | Anvil | Process shell commands over a distributed, asynchronous queue. | hyper-shell is a command-line terminal replacement that aims to enhance the user experience and productivity through various features and customizations. | Some core features of hyper-shell include customizable themes and plugins, multiple panes and tabs support, advanced text editing capabilities, built-in search functionality, and extensive keyboard shortcuts. | Command-Line Tool | Terminal Emulator, Productivity Tool, Command-Line Interface | Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/hyper-shell | Anvil: 2.0.2 | Productivity Tool | ||||||
hyperopt | Aces | Hyperopt's job is to find the best value of a scalar-valued, possibly-stochastic function over a set of possible arguments to that function. Description Source: https://hyperopt.github.io/hyperopt/getting-started/overview/ |
Hyperopt is a Python library for optimizing over arbitrary search spaces. The main goal of Hyperopt is to provide a flexible and expressive architecture for an optimization workforce, including hyperparameter optimization, machine learning and statistics. | 1. Distributed optimization: Hyperopt can distribute the optimization process across multiple compute nodes.\r 2. Parallel execution: Allows for parallel evaluation of the objective function.\r 3. Plug and play: Easily integrates with different Python libraries and frameworks, such as scikit-learn.\r 4. Support for various algorithms: Supports different optimization algorithms like TPE (Tree-structured Parzen Estimator) and random search.\r 5. Scalability: Can handle optimization problems with a large number of parameters efficiently. |
https://hyperopt.github.io/hyperopt/ | Optimization, Machine Learning, Statistics | https://github.com/hyperopt/hyperopt | Computer & Information Sciences | https://hyperopt.github.io/hyperopt/tutorials/01.BasicTutorial/ https://github.com/hyperopt/hyperopt/wiki/FMin |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.2.7 | Python Library | ||||
hyphen | Faster | Hyphen is a command-line tool for generating word hyphenation points using the TeX patterns. It can be used to improve the appearance of justified text by splitting words at appropriate points. | Generate Word Hyphenation Points, Utilizes Tex Patterns, Improves Text Justification | Utility Tool | Word Hyphenation, Text Formatting, Tex Patterns | Other Mathematics | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 20230104 | Text Formatting/Processing | |||||||
hyphy | Anvil | Hyphy is an open-source software package for the analysis of genetic sequences using techniques in phylogenetics, molecular evolution, and machine learning. | HyPhy (Hypothesis Testing using Phylogenies) is an open-source software package for the analysis of genetic sequences using techniques in phylogenetics, molecular evolution, and epidemiology. It provides a flexible and user-friendly platform for conducting evolutionary analysis on biological sequence data. | Phylogenetic Analysis, Selection Analysis, Recombination Analysis, Epidemiological Modeling, Population Genetics Analysis | Open-Source Software | Evolutionary Biology | Bioinformatics | Bioinformatics, Molecular Evolution, Phylogenetics, Epidemiology | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/hyphy | Anvil: 2.5.36 | Analysis Tool | ||||
hypo | Anvil | HyPo--a Hybrid Polisher-- utilises short as well as long reads within a single run to polish a long reads assembly of small and large genomes. | Hypo is a software package designed for statistical analysis and hypothesis testing. It provides a range of tools for conducting various types of statistical tests and analyzing data to determine the significance of results. | 1. Conducts hypothesis testing with a variety of statistical tests\r 2. Calculates p-values and confidence intervals\r 3. Supports both parametric and non-parametric tests\r 4. Provides tools for power analysis and sample size calculation\r 5. Offers data visualization capabilities for result interpretation |
Scientific Software | Statistical Analysis, Hypothesis Testing, Data Analysis | Statistics & Probability | Anvil: https://www.rcac.purdue.edu/software/hypo | Anvil: 1.0.3 | Statistical Analysis | ||||||
hypothesis | Aces, Faster | Hypothesis is a family of testing libraries which let you write tests parametrized by a source of examples. A Hypothesis implementation then generates simple and comprehensible examples that make your tests fail. Description Source: https://github.com/HypothesisWorks/hypothesis |
Hypothesis is a property-based testing tool for Python that helps in finding edge cases and identifying bugs by generating test data based on properties and invariants. | 1. Automatically generates test cases based on specified properties.\r 2. Provides comprehensive coverage by exploring a wide range of input values.\r 3. Identifies edge cases and corner scenarios that traditional testing might miss.\r 4. Integrates with popular testing frameworks like pytest.\r 5. Supports custom strategies for generating complex data structures. |
https://hypothesis.readthedocs.io/en/latest/ | Property-Based Testing Tool | Software Engineering, Systems, & Development | Computer Science | Python Testing Tool, Property-Based Testing, Automated Test Generation | https://github.com/HypothesisWorks/hypothesis | Computer & Information Sciences | https://hypothesis.works/articles/getting-started-with-hypothesis/ https://hypothesis.works/articles/incremental-property-based-testing/ https://hypothesis.readthedocs.io/en/latest/quickstart.html#where-to-start https://hypothesis.readthedocs.io/en/latest/examples.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.41.2, 6.13.1, 6.14.6, 6.46.7, 6.68.2, 6.82.0, 6.88.1, 6.90.0 Faster: 5.41.2, 5.41.5, 6.13.1, 6.14.6, 6.46.7, 6.68.2, 6.82.0 |
Testing Tool | |
hypre | Aces, Expanse, Faster, Stampede3 | HYPRE is a library of high performance preconditioners and solvers featuring multigrid methods for the solution of large, sparse linear systems of equations on massively parallel computers. Description Source: https://github.com/hypre-space/hypre |
HYPRE (High Performance Preconditioners) is a library of high performance preconditioners and solvers for the solution of large, sparse linear systems of equations on massively parallel computers. It provides scalable algorithms for solving large-scale scientific and engineering applications. | 1. Scalable algorithms for solving large-scale linear systems. 2. Preconditioners and solvers optimized for massively parallel computers. 3. Support for various parallel computing architectures. 4. Integration with other computational software and libraries. | https://hypre.readthedocs.io/en/latest/ | Computational Software | Numerical Computations | Applied Mathematics | Preconditioners, Solvers, Linear Systems, Sparse Matrices | https://github.com/hypre-space/hypre | Mathematics | https://hypre.readthedocs.io/en/latest/ch-intro.html#getting-more-information https://github.com/hypre-space/hypre/tree/master/src/examples https://github.com/hypre-space/hypre/wiki/Coding-Style |
Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 2.25.0, 2.27.0, 2.31.0 Expanse: Hj2Esdx, Jj2Ap7J, ... Faster: 2.18.2, 2.20.0, 2.21.0, 2.24.0, 2.25.0, 2.31.0 Stampede-3: 2.30.0-I64, 2.30.0 |
Library | |
iccifort | Faster | iccifort is a software tool that provides the Intel C++ and Fortran compilers for high-performance computing applications. These compilers are designed to optimize code performance for Intel processors. | Features include advanced optimization capabilities, support for the latest C++ and Fortran language standards, debugging and profiling tools, parallel computing support, vectorization, and compatibility with various operating systems. | Programming Tool | Compiler, High-Performance Computing, Optimization | Engineering & Technology | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2019.4.243, 2019.5.281, 2020.0.166, 2020.1.217, 2020.4.304 | Compiler | |||||||
iccifortcuda | Faster | ICCIFortCUDA is a high-performance computing (HPC) compiler designed for CUDA-enabled GPUs. It provides a set of tools for developers to write and compile parallel programs using NVIDIA’s CUDA architecture. | Hpc Compiler For Cuda-Enabled Gpus, Support For Parallel Programming, Optimized For Performance Tuning, Integration With Nvidia Cuda Architecture | Development Tools | Software Engineering, Systems, & Development | Computer Science | Hpc, Compiler, Cuda, Parallel Programming | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2020B | Compiler | |||||
icu | Aces, Faster | ICU is a mature, widely used set of C/C++ and Java libraries providing Unicode and Globalization support for software applications. | ICU (International Components for Unicode) is a mature, widely used set of C/C++ and Java libraries providing Unicode and Globalization support for software applications. ICU is utilized in a vast array of applications, operating systems, and devices to provide multilingual support. | 1. Comprehensive Unicode support for wide character and locale data.\r 2. String handling, collation, parsing, formatting, and transliteration capabilities.\r 3. Time zone and calendar functionality.\r 4. Text layout and bi-directional text support.\r 5. Language-specific support for various functionalities.\r 6. ICU data includes support for over 300 languages. |
https://unicode-org.github.io/icu/ | Libraries | Software Engineering, Systems, & Development | Unicode Support, Globalization, Localization, Internationalization, Unicode Libraries | https://icu.unicode.org/ | Computer & Information Sciences | https://unicode-org.github.io/icu/userguide/icu/howtouseicu.html https://icu4c-demos.unicode.org/icu-bin/icudemos |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 67.1, 69.1, 71.1, 72.1, 73.2 Faster: 64.2, 66.1, 67.1, 69.1, 71.1, 72.1, 73.2 |
Utility | ||
icu4c | Darwin, Kyric | ICU (International Components for Unicode) is a mature, widely used set of C/C++ and Java libraries providing Unicode and Globalization support for software applications. ICU is widely portable and gives applications the same results on all platforms and between C/C++ and Java software. | Unicode Support, Globalization Support, Cross-Platform Compatibility, C/C++ & Java Libraries | https://unicode-org.github.io/icu/ | Development | Unicode, Globalization, Cross-Platform, Libraries | https://icu.unicode.org/ | Computer & Information Sciences | https://unicode-org.github.io/icu/userguide/icu/howtouseicu.html https://icu4c-demos.unicode.org/icu-bin/icudemos |
Library | ||||||
idba | Anvil | Idba is a practical iterative De Bruijn Graph De Novo Assembler for sequence assembly in bioinfomatics. | IDBA (Iterative De Bruijn Graph Assembler) is a highly efficient and accurate de novo assembler for sequencing data, specifically designed for Illumina and/or 454 reads. It uses a novel iterative method to optimize the assembly of short reads into longer contigs, maintaining high accuracy and low memory consumption. | 1. De novo assembly of short sequencing reads. \r 2. Utilizes an iterative approach for optimizing assembly. \r 3. Designed for Illumina and 454 sequencing data. \r 4. High accuracy and low memory usage. \r 5. Handles complex and repetitive genomic regions effectively. |
Assembler | Genomics | Bioinformatics | De Novo Assembly, Sequencing Data, Illumina, 454, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/idba | Anvil: 1.1.3 | Ngs Assembly | ||||
idev | Stampede3 | The idev utility creates an interactive development environment from the user's login window. In the idev window the user is connected directly to a compute node from which the user can launch MPI-compiled executables directly (with the ibrun command). Description Source: https://tacc.utexas.edu/research/tacc-research/idev/ |
idev is a compiler wrapper that simplifies the use of Intel's data parallel C++ (DPC++) compiler for offloading computations to GPUs. | idev facilitates the compilation and execution of DPC++ code for GPU offloading, allowing developers to harness the power of GPUs for compute-intensive tasks. | https://docs.tacc.utexas.edu/software/idev/ | Tool | Applied Computer Science | Computer Science | Compiler Wrapper, Dpc++ Compiler, Gpu Offloading | https://tacc.utexas.edu/research/tacc-research/idev/ | Computer & Information Sciences | https://docs.tacc.utexas.edu/software/idev/#examples | Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ | Stampede-3: 2.0 | Compiler | |
idl | Darwin, Expanse, Stampede3 | IDL (Interactive Data Language) software is the trusted scientific programming language used across disciplines to create meaningful visualizations out of complex numerical data. From small-scale analysis programs to widely deployed applications, IDL provides the comprehensive computing environment you need to effectively get information from your data. Description Source: https://www.nv5geospatialsoftware.com/Products/IDL |
IDL (Interactive Data Language) is a programming language used for data analysis, visualization, and application development. It provides a comprehensive set of tools for scientific research and data processing. | IDL offers a wide range of mathematical functions, statistical analysis tools, image processing capabilities, and interactive graphics for data visualization. It supports data input/output operations, array handling, and extensive libraries for various scientific and engineering applications. | https://www.nv5geospatialsoftware.com/docs/using_idl_home.html | Programming Language | Software, Data Analysis, Data Visualization, Scientific Research | https://www.nv5geospatialsoftware.com/Products/IDL | Physical Sciences | https://www.nv5geospatialsoftware.com/docs/Command_Line_Options_for.html https://www.nv5geospatialsoftware.com/Learn/Videos/Video-Detail/PID/10263/mcat/18999/acat/2/evl/0/nsw/a/EDNSearch/idl |
Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Expanse: 8.4 Stampede-3: 8.4 |
Data Analysis & Visualization | |||
igenomes | Anvil | iGenomes is a collection of reference genomes and annotation files that have been pre-built for commonly used organisms, designed to streamline the data analysis pipeline for genomics research. | Pre-Built Reference Genomes, Annotation Files, Compatibility With Popular Bioinformatics Tools, Streamlined Data Analysis Process, Regularly Updated & Curated | Reference Genome & Annotation Repository | Bioinformatics, Genomics, Reference Genomes, Annotation, Data Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/igenomes | Anvil: 2023-04-26 | Bioinformatics Tool | |||||||
igprof | Aces | IgProf is a simple nice tool for measuring and analysing application memory and performance characteristics. | igprof is a lightweight, portable, and flexible performance profiling tool for C, C++, and Fortran applications. It provides insights into code performance and helps identify hotspots for optimization, with a focus on low-overhead and accurate measurements. | Lightweight & Portable Performance Profiler, Supports C, C++, & Fortran Applications, Low-Overhead Measurements For Accurate Profiling, Identifies Code Hotspots For Optimization, Offers Detailed Insights Into Application Performance | Tool | Profiler, Performance Analysis, Code Optimization, Software Development | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 5.9.18 Faster: 5.9.18 |
Performance Profiling | ||||||
igv | Anvil, Faster | The Integrative Genomics Viewer (IGV) is a high-performance, easy-to-use, interactive tool for the visual exploration of genomic data. It supports flexible integration of all the common types of genomic data and metadata, investigator-generated or publicly available, loaded from local or cloud sources. Description Source: https://igv.org/doc/desktop/ |
Integrative Genomics Viewer (IGV) is a high-performance visualization tool for interactive exploration of large, diverse genomics data sets. It supports a wide variety of data types, including next-generation sequencing data, microarrays, and genomic annotations. | IGV allows users to visualize and analyze genomic data through an interactive and user-friendly interface. Users can view aligned reads, gene expression data, variant calls, copy number variations, and more. It supports various file formats such as BAM, VCF, BED, and GFF. Users can also customize the display settings, zoom in on specific regions, and compare multiple samples side by side. | https://igv.org/doc/desktop/#UserGuide/advanced/command_line/ | Genomics Software | Visualization, Genomics, Sequencing, Data Analysis | https://igv.org/ | Biological Sciences | https://www.youtube.com/channel/UCb5W5WqauDOwubZHb-IA_rA https://igv.org/doc/desktop/#QuickStart/#2-load-a-reference-genome |
Anvil: https://www.rcac.purdue.edu/software/igv Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 2.11.9, 2.12.3 Faster: 2.9.4-Java-11 |
Visualization Tool | |||
iimkl | Faster | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2022B | |||||||||||||
iimpi | Aces, Faster | iimpi is EasyBuild support for intel compiler toolchain (includes Intel compilers (icc, ifort), Intel MPI). Description Source: https://docs.easybuild.io/api/easybuild/toolchains/iimpi/ |
IIMPI (Isobaric Ion Mobility Mass Spectrometry with Peak Integration) is a software tool specifically designed for analyzing ion mobility-mass spectrometry data with a focus on accurate peak integration in the presence of isobaric co-elution. | 1. Accurate peak integration in ion mobility-mass spectrometry data. 2. Specialized functionality for handling isobaric co-elution. 3. User-friendly interface for efficient data analysis. | https://docs.easybuild.io/api/easybuild/toolchains/iimpi/ | Analytical Tool | Proteomics | Bioinformatics | Ion Mobility-Mass Spectrometry, Peak Integration, Data Analysis | https://docs.easybuild.io/api/easybuild/toolchains/iimpi/ | Biological Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2021B, 2022A, 2022B, 2022.12, 2023A, 2023B, 2023.03, 2023.07 Faster: 2019B, 2020A, 2020B, 2020.12, 2021A, 2021B, 2022A, 2022B, 2022.00, 2022.05, 2022.09, ... |
Data Analysis | ||
iimpic | Faster | iimpic is a Python library for multi-scale modeling of porous materials using the lattice Boltzmann method (LBM). It provides a versatile platform for simulating flow and transport phenomena in complex porous media. | 1. Implementation of the lattice Boltzmann method for porous media simulations. 2. Multi-scale modeling capabilities. 3. User-friendly Python interface for easy implementation and customization. 4. Support for various boundary conditions and fluid-solid interactions. | Simulation Software | Condensed Matter Physics | Physical Sciences | Python Library, Porous Materials, Lattice Boltzmann Method | Physical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2020B | Computational Software | |||||
imageio | Aces, Faster | Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, volumetric data, and scientific formats. It is cross-platform, runs on Python 3.5+, and is easy to install. Description Source: https://imageio.readthedocs.io/en/stable/ |
Imageio is a Python library that provides an easy interface to read and write a wide range of image and video file formats. It allows for simple, high-level access to image data from Python code. | 1. Read and write images in various formats such as JPEG, PNG, BMP, GIF, and more.\r 2. Support for reading and writing videos in formats like MPEG, AVI, and QuickTime.\r 3. Integration with NumPy arrays for efficient image processing.\r 4. Easily display, save, and manipulate images in Python applications.\r 5. Simple and uniform API for accessing image data across multiple formats. |
https://imageio.readthedocs.io/en/stable/ | Python Library | Python Libraries, Image Processing, Data Visualization | https://github.com/imageio/imageio | Computer & Information Sciences | https://imageio.readthedocs.io/en/stable/examples.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.22.2 Faster: 2.9.0, 2.13.5, 2.22.2 |
Library | |||
imagej | Aces, Faster | ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh. It runs, either as an online applet or as a downloadable application, on any computer with a Java 1.4 or later virtual machine. Description Source: https://imagej.net/ij/docs/intro.html |
ImageJ is a public domain, Java-based image processing program developed at the National Institutes of Health. It is widely used for scientific image analysis and visualization. | Image Processing, Image Analysis, Visualization Tools, Macro Recording & Scripting, Plugin Support For Extensibility | https://imagej.net/ij/docs/guide/ | Image Processing, Scientific Tool, Java-Based, Open-Source | https://imagej.net/ | https://imagej.net/tutorials/ https://imagej.net/imaging/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.53T-Java-11 Faster: 1.54B-Java-1.8 |
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imagemagick | Aces, Delta, Expanse, Faster, Ookami | ImageMagick is a free, open-source software suite, used for editing and manipulating digital images. It can be used to create, edit, compose, or convert bitmap images, and supports a wide range of file formats, including JPEG, PNG, GIF, TIFF, and PDF. | ImageMagick is a free and open-source software suite for creating, editing, composing, or converting bitmap images. | Supports A Wide Range Of Image Formats, Batch Processing, Image Editing & Manipulation, Conversion Between Different Image Formats, Command-Line Interface | https://imagemagick.org/script/command-line-tools.php | Utility | Image Processing, Graphics Editing, Conversion Tool | https://imagemagick.org/index.php | Computer & Information Sciences | https://imagemagick.org/Usage/ | Aces: https://hprc.tamu.edu/software/aces/ Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 7.0.11-14, 7.1.0-4, 7.1.0-37, 7.1.0-53, 7.1.1-15 Delta: 6.9, 7.1.0 Expanse: E46Spvd, ... Faster: 7.0.10-1, 7.0.10-35, 7.0.11-14, 7.1.0-4, 7.1.0-37, 7.1.0-53 Ookami: 7.1.0 |
Image Processing | |||
imake | Aces | imake is a Makefile-generator that is intended to make it easier to develop software portably for multiple systems. | imake is a software tool that automates the construction of imakefiles, which are used with the make utility in software development projects. It simplifies the process of generating makefiles for building software projects, allowing developers to focus on writing code rather than manually creating build configurations. | 1. Automates the generation of makefiles for software projects\r 2. Allows developers to define rules for compiling source code and linking executable\r 3. Simplifies the build configuration process\r 4. Supports customization for specific project requirements\r 5. Integrates with the make utility for building software projects |
Automation Tool | Software Engineering, Systems, & Development | Build Automation, Software Development, Build Configuration | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.0.8 | Build Tools | |||||
imath | Aces, Faster | Imath is a basic, light-weight, and efficient C++ representation of 2D and 3D vectors, 2x2, 3x3, and 4x4 matrices, and other simple but useful mathematical objects, functions, and data types common in computer graphics applications, including the half 16-bit floating-point type. Description Source: https://imath.readthedocs.io/en/latest/ |
iMath is a comprehensive computational software for mathematical modeling, simulation, and analysis. It provides a user-friendly interface for performing various mathematical and statistical computations. | Some core features of iMath include symbolic and numeric computation capabilities, data visualization tools, equation solving, optimization algorithms, statistical analysis functions, and support for matrix operations. | https://imath.readthedocs.io/en/latest/ | Mathematical Modeling & Analysis Software | Mathematics, Computational Software, Simulation, Data Analysis | https://github.com/AcademySoftwareFoundation/Imath | Mathematics | https://imath.readthedocs.io/en/latest/concepts.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.1.5, 3.1.6, 3.1.7 Faster: 3.1.5, 3.1.6, 3.1.7 |
Computational Software | |||
imb | Kyric | IMB stands for In-Memory Database benchmark. It is a benchmarking tool specifically designed to evaluate the performance of in-memory databases. | IMB allows users to compare different in-memory databases based on various performance metrics such as transaction throughput, response times, and scalability. It provides a standardized testing environment to ensure fair comparisons between different database systems. | https://imbalanced-learn.org/stable/references/index.html#api | Tool | Benchmarking, In-Memory Databases | https://imbalanced-learn.org/stable/ | Computer & Information Sciences | https://imbalanced-learn.org/stable/user_guide.html#user-guide https://imbalanced-learn.org/stable/install.html#getting-started https://imbalanced-learn.org/stable/auto_examples/index.html#general-examples |
Kyric: 2019.6 | Benchmarking | |||||
imbalanced-learn | Aces | Imbalanced-learn (imported as imblearn) is an open source, MIT-licensed library relying on scikit-learn (imported as sklearn) and provides tools when dealing with classification with imbalanced classes. Description Source: https://imbalanced-learn.org/stable/ |
Imbalanced-learn is a Python library designed to tackle the problem of imbalanced datasets in machine learning. It provides a set of tools and techniques to deal with classification tasks where the distribution of classes is skewed, with one class significantly more frequent than the others. | Over-Sampling Techniques (Smote, Adasyn, Etc.), Under-Sampling Techniques, Combined Over-Sampling & Under-Sampling, Ensemble Techniques (Balancedrandomforestclassifier, Rusboostclassifier), Cost-Sensitive Learning, Support For Scikit-Learn Pipeline Integration | https://imbalanced-learn.org/stable/references/index.html#api | Python Library | Artificial Intelligence & Intelligent Systems | Imbalanced Datasets, Machine Learning, Classification Tasks, Python Library, Over-Sampling, Under-Sampling, Ensemble Techniques | https://imbalanced-learn.org/stable/ | Computer & Information Sciences | https://imbalanced-learn.org/stable/user_guide.html#user-guide https://imbalanced-learn.org/stable/install.html#getting-started https://imbalanced-learn.org/stable/auto_examples/index.html#general-examples |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.10.1 | Data Analysis | ||
imkl | Aces, Faster | The Intel® oneAPI Math Kernel Library (oneMKL) helps you achieve maximum performance with a math computing library of highly optimized, extensively parallelized routines for CPU and GPU. The library has C and Fortran interfaces for most routines on CPU, and SYCL interfaces for some routines on both CPU and GPU. Description Source: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html#gs.4ofwv9 |
imkl is a open-source software library for creating and managing knowledge graphs for various applications in artificial intelligence, data science, and information retrieval. | The core features of imkl include graph creation, visualization, querying, and analysis functionality for knowledge graphs. It provides tools for integrating heterogeneous data sources, performing entity recognition and disambiguation, and inferring relationships between entities. | https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2024-1/overview.html | Open-Source | Software Library, Knowledge Graph, Artificial Intelligence, Data Science, Information Retrieval | https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html | Computer & Information Sciences, Artificial Intelligence & Intelligent Systems | https://github.com/oneapi-src/oneAPI-samples/tree/master/Libraries/oneMKL/matrix_mul_mkl https://github.com/oneapi-src/oneAPI-samples/tree/master/Libraries/oneMKL/block_cholesky_decomposition https://www.intel.com/content/www/us/en/docs/onemkl/get-started-guide/2024-1/overview.html#GUID-618F67AE-A641-4F48-80E6-AD6D9E70FA2F |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2021.4.0, 2022.1.0, 2022.2.1, 2023.0.0, 2023.1.0, 2023.2.0, 2024.0.0 Faster: 2019.5.281, 2020.1.217, 2020.4.304, 2021.1.1, 2021.2.0, 2021.3.0, 2021.4.0, 2022.0.1, 2022.1.0, 2022.2.0, ... |
Library | |||
imkl-fftw | Aces, Faster | FFTW is a free collection of C routines for computing the discrete Fourier Transform (DFT) in one or more dimensions, and provides portability across platforms. The Intel Math Kernel Library (MKL) offers FFTW2 (for version 2.x) and FFTW3 (for version 3.x) interfaces to the Intel MKL Fast Fourier Transform and Trigonometric Transform functionality. These interfaces enable applications using FFTW to gain performance with Intel MKL without changing the application source code. Description Source: https://www.nas.nasa.gov/hecc/support/kb/mkl-fftw-interface_204.html |
imkl-fftw is a library that combines Intel Math Kernel Library (IMKL) with FFTW (Fastest Fourier Transform in the West) for high-performance computation of Fourier transforms on Intel architectures. | 1. Integration of Intel Math Kernel Library (IMKL) for optimized mathematical functions.\r 2. Utilizes the Fastest Fourier Transform in the West (FFTW) for efficient Fourier transform computations.\r 3. High performance on Intel architectures for Fourier transform operations. |
Mathematical Computation | Software Library, Math Library, Mathematical Computation, Fourier Transforms, High-Performance Computing | https://www.nas.nasa.gov/hecc/support/kb/mkl-fftw-interface_204.html | Mathematics | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2021.4.0, 2022.1.0, 2022.2.1, 2023.0.0, 2023.1.0, 2023.2.0 Faster: 2021.4.0, 2022.0.1, 2022.1.0, 2022.2.0, 2022.2.1, 2023.0.0, 2023.1.0, ... |
Library | |||||
iml | Aces | IML is a free library of C source code which implements algorithms for computing exact solutions to dense systems of linear equations over the integers. | Interpretable Machine Learning | iml is an R package that enables interpretable machine learning for regression and classification models. It provides a suite of tools for understanding the predictions of machine learning models by creating interpretable explanations. | R Package | Machine Learning, Interpretability, Model Explanation | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 1.0.5 | Machine Learning Interpretability | ||||||
impi | Aces, Anvil, Faster, Stampede3 | impi is an intel MPI implementation. It is included in the Intel-2017.4 compiler. It is a good compiler for MPI programming on Xeon Phi. Description Source: https://hpc.loni.org/docs/guides/software.php?software=impi# |
impi is a high-performance message passing library that provides asynchronous messaging and queuing functionalities for parallel computing applications. | impi offers efficient communication among processes, supports scalable performance for large-scale parallel computing, and has advanced queuing mechanisms for managing message passing in distributed computing environments. | https://www.intel.com/content/www/us/en/docs/mpi-library/developer-reference-linux/2021-12/overview.html | Communication Library | Message Passing Library, Parallel Computing, Asynchronous Messaging | https://www.intel.com/content/www/us/en/developer/tools/oneapi/mpi-library.html#gs.5295ue | Engineering & Technology | https://www.intel.com/content/www/us/en/docs/mpi-library/get-started-guide-linux/2021-11/overview.html | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/impi Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 2021.4.0, 2021.6.0, 2021.7.1, 2021.8.0, 2021.9.0, 2021.10.0, 2021.11.0 Anvil: 2019.5.281 Faster: 2018.5.288, 2019.7.217, 2019.9.304, 2021.1.1, 2021.2.0, 2021.3.0, 2021.4.0, 2021.5.0, 2021.6.0, 2021.7.0, ... Stampede-3: 21.9, 21.11 |
Library | |||
impute2 | Anvil | Impute2 is a genotype imputation and haplotype phasing program. | IMPUTE2 is a tool for imputing ungenotyped markers in large-scale genome-wide association studies. | IMPUTE2 uses a combination of reference haplotypes and the study genotypes to infer genotypes at ungenotyped SNPs. It also provides a quality score to assess the imputation accuracy. The software supports a variety of input formats and allows for parallel computing to speed up the imputation process. | Tool | Genome-Wide Association Studies | Genetics | Genotype Imputation, Genome-Wide Association Studies, Bioinformatics | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/impute2 | Anvil: 2.3.2 | Bioinformatics | ||||
infernal | Anvil, Bridges-2 | Infernal ("INFERence of RNA ALignment") is for searching DNA sequence databases for RNA structure and sequence similarities. It is an implementation of a special case of profile stochastic context-free grammars called covariance models (CMs). A CM is like a sequence profile, but it scores a combination of sequence consensus and RNA secondary structure consensus, so in many cases, it is more capable of identifying RNA homologs that conserve their secondary structure more than their primary sequence. Description Source: http://eddylab.org/infernal/ |
Infernal is a software for searching DNA sequence databases for RNA structure and sequence similarities. It is used to align RNA sequences to RNA sequence and structural models. | 1. Searching DNA sequence databases for RNA structure and sequence similarities\r 2. Aligning RNA sequences to RNA sequence and structural models\r 3. Building covariance models\r 4. Detecting RNA homologs |
http://eddylab.org/infernal/Userguide.pdf | RNA Sequence Analysis, Bioinformatics, Sequence Alignment | http://eddylab.org/infernal/ | https://github.com/EddyRivasLab/infernal/blob/master/documentation/userguide/tutorial.tex | Anvil: https://www.rcac.purdue.edu/software/infernal Bridges-2: https://www.psc.edu/resources/software/infernal |
Anvil: 1.1.4 Bridges-2: 1.1.3 |
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init_opencl | Kyric | init_opencl is a software library that is used to initialize OpenCL platforms and create OpenCL contexts for parallel computing applications. | Initialize Opencl Platforms, Create Opencl Contexts, Support For Parallel Computing Applications | Software Development | Software, Compiler, Library, Hpc | Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Library | ||||||||
inputproto | Delta | A package that provides the headers used to compile Xlib clients. | Provides the necessary headers for compiling Xlib clients. | Library | Software Development, Headers, Xlib | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 2.3.2 | Development Tools | |||||||
inq | Faster | inq is a command-line tool for managing and querying inventory data in YAML format. It allows users to easily manipulate and search inventory data for system administration tasks. | Create & Manage Inventory Data In Yaml Format, Query Inventory Data Using A Simple Command-Line Interface, Use Filters & Search Queries To Extract Specific Information, Facilitates System Administration Tasks Related To Inventory Management | Command-Line Interface | Inventory Management, System Administration | Computer & Information Sciences, Other Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 20230821 | Tools | |||||||
inspector | Kyric | Inspector is a software tool used for monitoring and analyzing various aspects of computer systems and networks to detect and prevent security breaches or performance issues. | Key features include real-time monitoring of network traffic, system performance metrics, and security events. It provides alerts for suspicious activities, generates reports for analysis, and allows for proactive response to potential threats. | https://www.intel.com/content/www/us/en/docs/inspector/user-guide-linux/2024-1/overview.html | Security Software | Software Engineering, Systems, & Development | Computer Science | Monitoring, Security, Network Analysis | https://www.intel.com/content/www/us/en/developer/tools/oneapi/inspector.html#gs.52c03e | Computer & Information Sciences | https://www.intel.com/content/www/us/en/docs/inspector/get-started-guide/2024-1/linux.html https://www.intel.com/content/www/us/en/developer/articles/training/inspector-tutorials.html |
Kyric: Latest, 2021.1.1 | Monitoring Tool | |||
instrain | Anvil | Instrain is a python program for analysis of co-occurring genome populations from metagenomes that allows highly accurate genome comparisons, analysis of coverage, microdiversity, and linkage, and sensitive SNP detection with gene localization and synonymous non-synonymous identification. | instrain is a python package for identifying strains in metagenomic data. It allows users to infer strain-level composition of metagenomes and identify variants specific to different strains within a microbial community. | 1. Strain-level composition identification in metagenomic data\r 2. Variant identification specific to different strains within a microbial community\r 3. Analysis of strain heterogeneity and evolution within microbial populations |
Python Library | Metagenomics, Microbial Ecology | Bioinformatics | Metagenomics, Microbial Community, Strain Identification, Variant Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/instrain | Anvil: 1.5.7, 1.6.3 | Library | ||||
intarna | Anvil | Intarna is a general and fast approach to the prediction of RNA-RNA interactions incorporating both the accessibility of interacting sites as well as the existence of a user-definable seed interaction. | IntaRNA predicts RNA-RNA interactions by taking both target site accessibility and hybridization energies into account, allowing the identification of interaction sites that are not only energetically favorable, but also accessible in the target RNA. | 1. Prediction of RNA-RNA interactions\r 2. Consideration of target site accessibility\r 3. Calculation of hybridization energies\r 4. Identification of energetically favorable interaction sites\r 5. Accessibility calculation in target RNA |
Bioinformatics Tool | Bioinformatics | Biological Sciences | RNA-RNA Interaction Prediction, Bioinformatics, RNA Structure Prediction | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/intarna | Anvil: 3.3.1 | Prediction Tool | ||||
intel | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Kyric, Stampede3 | Intel Compilers. Intel Parallel Studio XE 2020 Cluster Edition is an advanced, comprehensive C ++ and Fortran tool suite that simplifies and speeds HPC and cluster application development , debug, and tuning. | Intel is a multinational corporation that designs and manufactures semiconductor chips and other technology products. The company is a leading provider of microprocessors for personal computers, servers, and other computing devices. | Intel offers a wide range of products including processors, integrated graphics solutions, system-on-chip products, and more. Their technology powers a variety of devices and applications across different industries. | Hardware | Semiconductor, Technology, Microprocessors | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/intel Bridges-2: https://www.psc.edu/resources/software/intel Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ |
Aces: 2023.1.0, 2023.2.0, 2023.2.0.231103 Anvil: 19.0.5.281 Bridges-2: 20.4, 2021.3.0, 2021.10.0 Delta: 2022.2.1, 2024.0.0 Expanse: Vecir2B, 6Pv46So Faster: Toolkits, 2019B, 2020A, 2020B, 2020.12, 2021A, 2021B, 2022A, 2022B, 2022.00, 2022.05, ... Kyric: 19.1.3.304 Ookami: Tbb/64/2020/20.0.2 Stampede-3: 23.1, 24.0 |
Enterprise Software | ||||||
intel compiler | Jetstream | The Intel Compiler is a suite of high-performance compilers from Intel for various programming languages, including C, C++, and Fortran. It is designed to maximize application performance on Intel architecture-based processors. | The Intel Compiler provides advanced optimization features to enhance application performance, including auto-vectorization, parallelization, and profile-guided optimization. It supports the latest language standards and includes tools for debugging and performance analysis. | Development Tools | Compiler, Optimization, Performance, Debugging | Computer & Information Sciences | Compiler | |||||||||
intel_ai_toolkit | Delta | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 2023.1 | Compilers | ||||||||||||
intel_ipp_ia32 | Kyric | Kyric: Latest, 2021.1.1 | Compilers | |||||||||||||
intel_ipp_intel64 | Kyric | Intel Integrated Performance Primitives (Intel IPP) provides high-performance software libraries that are designed to help developers improve the performance of their applications. Intel IPP offers a wide range of functions that are optimized for Intel architecture, including signal, imaging, cryptography, and data processing algorithms. | 1. Optimized functions for signal processing, imaging, cryptography, and data processing. 2. Support for various data formats and algorithms. 3. High performance on Intel architecture. 4. Multi-threading and SIMD support for parallel processing. 5. Integration with popular development environments and languages. | Commercial | Software Development, Performance Optimization, Data Processing, Signal Processing, Image Processing, Cryptography | Computer & Information Sciences, Software Engineering, Systems, & Development | Kyric: Latest, 2021.1.1 | Library | ||||||||
intel_ippcp_ia32 | Kyric | Intel Integrated Performance Primitives - Cryptography (IPP-Crypto) is a library that provides highly optimized building blocks for a variety of encryption and decryption algorithms on Intel architecture processors. It aims to accelerate cryptographic operations to enhance performance in software applications. | Optimized Encryption & Decryption Algorithms, Support For Various Cryptographic Techniques, Designed For Intel Architecture Processors, Improved Performance In Cryptographic Operations | Compiler/Library | Cryptographic Library, Performance Optimization, Intel Architecture | Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Library | ||||||||
intel_ippcp_intel64 | Kyric | Intel Integrated Performance Primitives Cryptography (IPP Cryptography) is a collection of highly optimized cryptographic functions and algorithms developed by Intel for high-performance computing applications. It provides a set of cryptographic functions optimized for Intel processors to enhance the security and performance of cryptographic operations in software. | Optimized Cryptographic Functions For Intel Processors, High-Performance Encryption & Decryption Algorithms, Support For A Variety Of Cryptographic Operations, Integration With Intel Ipp Library For Additional Performance Optimizations | Optimization Library | Cryptography, High-Performance Computing, Intel Processors, Security | Computer & Information Sciences | Kyric: Latest, 2021.1.1 | Library | ||||||||
intel-advisor | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-advisor | Bridges-2: 2023.2.0 | |||||||||||||
intel-ccl | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-ccl | Bridges-2: 2021.10.0 | |||||||||||||
intel-compiler | Bridges-2 | The Intel Compiler suite is a set of optimizing compilers with support for C, C++, and Fortran languages. It provides advanced optimizations and performance tuning for applications running on Intel architecture-based platforms. | 1. Advanced optimizations for Intel processors\r 2. Support for C, C++, and Fortran languages\r 3. Performance tuning capabilities\r 4. Vectorization and parallelization support\r 5. Interoperability with existing codebases\r 6. Integration with Intel architecture-based platforms |
Development Tools | Software Engineering, Systems, & Development | Computer Science | Compiler, Optimization, Performance, Parallelization | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-compiler | Bridges-2: 2023.2.1 | Compiler | |||||
intel-compiler-rt | Bridges-2 | The Intel Compiler Runtime Library (Intel Compiler RT) is a collection of runtime libraries for the Intel software development tools, designed to provide support for various runtime components in software applications compiled with Intel compilers. | 1. Provides runtime support for applications compiled with Intel compilers\r 2. Includes optimized libraries for performance-critical functions\r 3. Supports advanced processor optimizations\r 4. Enhances application performance and reliability\r 5. Enables better scalability and parallelism |
Compiler Runtime Library | Compiler, Runtime Library, Performance Optimization | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-compiler-rt | Bridges-2: 2023.2.1 | Library | |||||||
intel-compiler-rt32 | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-compiler-rt32 | Bridges-2: 2023.2.1 | |||||||||||||
intel-compiler32 | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-compiler32 | Bridges-2: 2023.2.1 | |||||||||||||
intel-compilers | Aces, Faster | Intel C, C++ & Fortran compilers (classic and oneAPI) | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2021.2.0, 2021.4.0, 2022.1.0, 2022.2.0, 2022.2.1, ... Faster: 2021.1.2, 2021.2.0, 2021.3.0, 2021.4.0, 2022.0.1, ... |
Compilers | |||||||||||
intel-dal | Bridges-2 | Intel Dynamic Application Loader (DAL) is a framework that enables applications to dynamically load and execute small code modules. It provides a secure environment for executing trusted applications on Intel platforms. | 1. Secure environment for executing trusted applications\r 2. Ability to dynamically load and execute small code modules\r 3. Provides isolation and protection mechanisms\r 4. Streamlines the process of developing and deploying applications\r 5. Supports multiple platforms and languages |
Security, Intel Platform, Dynamic Code Loading, Trusted Applications | Bridges-2: https://www.psc.edu/resources/software/intel-dal | Bridges-2: 2023.2.0 | ||||||||||
intel-debugger | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-debugger | Bridges-2: 2023.2.0 | |||||||||||||
intel-dev-utilities | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-dev-utilities | Bridges-2: 2021.10.0 | |||||||||||||
intel-dnnl | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-dnnl | Bridges-2: 2023.2.0 | |||||||||||||
intel-dnnl-cpu-gomp | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-dnnl-cpu-gomp | Bridges-2: 2023.2.0 | |||||||||||||
intel-dnnl-cpu-iomp | Bridges-2 | The Intel oneAPI Deep Neural Network Library (DNNL) for CPU with Intel oneAPI Math Kernel Library (iomp) is a high-performance library for deep learning applications optimized for Intel CPUs. It provides highly optimized functions for deep learning frameworks and applications to accelerate training and inference tasks. | 1. Accelerated deep learning operations on Intel CPUs.\r 2. Integration with deep learning frameworks like TensorFlow and PyTorch.\r 3. Support for various neural network layer types.\r 4. Enhanced performance through optimizations for Intel architecture.\r 5. Scalability for large-scale deep learning models. |
Tool | Deep Learning, Cpu Optimization, Neural Networks | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-dnnl-cpu-iomp | Bridges-2: 2023.2.0 | Library | |||||||
intel-dnnl-cpu-tbb | Bridges-2 | Intel oneAPI Deep Neural Network Library (DNNL) for CPU with Threading Building Blocks (TBB) support is a high-performance library for deep learning applications. It provides optimized building blocks for implementing deep neural networks on Intel CPUs. | 1. High-performance deep learning library optimized for Intel CPUs. 2. Supports various neural network models and operations. 3. Integration with Threading Building Blocks (TBB) for efficient multi-threading. 4. Provides primitives for deep learning acceleration on Intel CPUs. | Deep Learning Library | Machine Learning | Artificial Intelligence & Intelligent Systems | Deep Learning, Neural Networks, Cpu Optimization, Threading Building Blocks | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-dnnl-cpu-tbb | Bridges-2: 2023.2.0 | Library | |||||
intel-dpct | Bridges-2 | Intel Data Parallel C++ (DPC++) Compatibility Tool (dpct) is a tool developed by Intel to facilitate migration of CUDA kernels to Data Parallel C++ (DPC++) for seamless porting to heterogeneous platforms. | 1. Automatic translation of CUDA source code to DPC++ source code. 2. Support for CUDA kernels defined in separate files. 3. Generation of DPC++ offload syntax for given CUDA kernel code. 4. Integration with Intel Advisor & Inspector tools for analysis and optimization of the code. 5. Compatible with Intel oneAPI toolkits for cross-architecture development. | Compiler | Intel, Data Migration, Cuda, Dpc++, Heterogeneous Computing | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-dpct | Bridges-2: 2023.2.0 | Tool | |||||||
intel-dpl | Bridges-2 | Intel-DPL (Data Parallel Library) is a software library that enables developers to write parallel programs in a natural and expressive way, without needing to have expertise in parallel programming. It helps in achieving high performance in parallel computing tasks by utilizing task parallelism and data parallelism. | Easy-To-Use Parallel Programming Interface, Support For Task Parallelism & Data Parallelism, High Performance Computing Capabilities, Optimized For Intel Architectures | Development Tool | Parallel Programming, High Performance Computing, Intel Architecture | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-dpl | Bridges-2: 2022.2.0 | Parallel Programming Library | |||||||
intel-icc | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-icc | Bridges-2: 2023.2.1 | |||||||||||||
intel-icc32 | Bridges-2 | The intel-icc32 compiler is a part of the Intel Compiler Suite specifically designed for 32-bit architectures. It provides a set of tools and libraries for optimizing and building applications for Intel processors. | 1. Support for 32-bit architectures\r 2. Optimization for Intel processors\r 3. Building and compiling applications\r 4. Integration with Intel libraries\r 5. Parallel computing support |
Development Tools | Compiler, Software Development, Optimization | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-icc32 | Bridges-2: 2023.2.1 | Compiler | |||||||
intel-inspector | Bridges-2 | The Intel Inspector is a dynamic memory and threading error checking tool for users developing serial and multithreaded applications on Windows or Linux operating systems. It helps developers find memory and threading errors early in the code development cycle to eliminate costly and time-consuming issues that might otherwise arise later in the development phase or in the field. | 1. Detects memory leaks and errors in multithreaded applications.\r 2. Provides highly detailed error analysis and debugging capabilities.\r 3. Supports serial and multithreaded applications on Windows and Linux platforms.\r 4. Offers comprehensive data race and deadlock detection. |
Memory & Threading Error Checker | Software, Development, Debugging, Memory Management, Multithreading | Engineering & Technology | Bridges-2: https://www.psc.edu/resources/software/intel-inspector | Bridges-2: 2023.2.0 | Debugging Tool | |||||||
intel-ipp-ia32 | Bridges-2 | Intel Integrated Performance Primitives (Intel IPP) for IA-32 architecture is a software library that provides a comprehensive set of high-performance functions for building advanced applications in various domains. It offers optimized routines for signal and data processing, image processing, cryptography, and more. | 1. Optimized routines for signal and data processing.\r 2. High-performance functions for image processing.\r 3. Cryptography functions for secure data handling.\r 4. Support for various domains and applications.\r 5. Platform-specific optimizations for IA-32 architecture. |
Shared Library | Software Engineering, Systems, & Development | Computer Science | Software Library, Performance Optimization, Signal Processing, Image Processing, Cryptography | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-ipp-ia32 | Bridges-2: 2021.9.0 | Library | |||||
intel-ipp-intel64 | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-ipp-intel64 | Bridges-2: 2021.9.0 | |||||||||||||
intel-ippcp-ia32 | Bridges-2 | Intel Integrated Performance Primitives (IPP) Cryptography (IPP-Crypto) is a library of high-performance cryptographic and security functions optimized for Intel processors. It provides developers with a broad range of encryption, digital signature, and authentication functionality to secure data and communications. | 1. Optimized cryptographic functions for encryption and decryption.\r 2. Support for digital signatures and authentication mechanisms.\r 3. Accelerated performance on Intel processors.\r 4. Broad range of cryptographic algorithms, including AES, RSA, and SHA. |
Program Library | Software Library, Cryptography, Security | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-ippcp-ia32 | Bridges-2: 2021.8.0 | Library | |||||||
intel-ippcp-intel64 | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-ippcp-intel64 | Bridges-2: 2021.8.0 | |||||||||||||
intel-itac | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-itac | Bridges-2: 2021.10.0 | |||||||||||||
intel-mkl | Anvil, Bridges-2, Darwin, Expanse | Intel Math Kernel Library (MKL) contains ScaLAPACK, LAPACK, Sparse Solver, BLAS, Sparse BLAS, CBLAS, GMP, FFTs, DFTs, VSL, VML, and Interval Arithmetic routines. | https://www.intel.com/content/www/us/en/resources-documentation/developer.html#gs.5q9gn8 | https://www.rcac.purdue.edu/index.php/knowledge/applications/intel-mkl | Anvil: https://www.rcac.purdue.edu/software/intel-mkl Bridges-2: https://www.psc.edu/resources/software/intel-mkl Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 2019.5.281, 2020.4.304 Bridges-2: 2023.2.0 Expanse: Flrwt2M, ... |
Compilers | |||||||||
intel-mkl32 | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-mkl32 | Bridges-2: 2023.2.0 | |||||||||||||
intel-mpi | Bridges-2, Expanse | Bridges-2: https://www.psc.edu/resources/software/intel-mpi Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Bridges-2: 2021.10.0 Expanse: Ezrfjne, ... |
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intel-oclfpga | Bridges-2 | The Intel OneAPI Base Toolkit for OpenCL FPGA is a comprehensive suite of development tools for accelerating workloads on Intel FPGA devices. It provides a unified programming model for CPU, GPU, and FPGA to simplify application development and deployment across diverse hardware architectures. | Unified Programming Model For Cpu, Gpu, & Fpga, Optimized Performance For Intel Fpga Devices, Support For Opencl Programming Language, Integration With Intel Oneapi Base Toolkit | Compiler | Software Engineering, Systems, & Development | Computer Science | Development Tools, Accelerating Workloads, Fpga Programming, Hardware Acceleration | Computer & Information Sciences | Bridges-2: https://www.psc.edu/resources/software/intel-oclfpga | Bridges-2: 2023.2.1 | Development Tools | |||||
intel-oneapi | Bridges-2, Darwin | Bridges-2: https://www.psc.edu/resources/software/intel-oneapi | Bridges-2: 2023.2.1 Jetstream: 2023.0.0 |
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intel-oneapi-advisor | Delta | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 2024.0.0 | Compilers | ||||||||||||
intel-oneapi-compilers | Delta | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 2022.2.1, ... | Compilers | ||||||||||||
intel-oneapi-mkl | Darwin, Delta | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 2024.0.0 | Compilers | ||||||||||||
intel-oneapi-mpi | Delta | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 2021.11.0 | |||||||||||||
intel-python | Darwin, Faster | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2022.1.0 | |||||||||||||
intel-tbb | Bridges-2, Delta, Expanse | Bridges-2: https://www.psc.edu/resources/software/intel-tbb Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Bridges-2: 2021.10.0 Delta: 2021.9.0 Expanse: 2020.3 |
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intel-tbb32 | Bridges-2 | Intel Threading Building Blocks (TBB) is a widely-used C++ library for parallelism. It provides a way to write parallel C++ programs that take full advantage of multi-core processors. | 1. Parallel algorithms and containers for C++.\r 2. Task scheduler framework for managing parallel workloads.\r 3. Scalability features for efficient multi-core utilization.\r 4. Portable and easy-to-use API for developers. |
Library | Parallelism, C++, Multi-Core, Library | Computer & Information Sciences, Computer Science, Applied Computer Science | Bridges-2: https://www.psc.edu/resources/software/intel-tbb32 | Bridges-2: 2021.10.0 | Development Tools | |||||||
intel-vtune | Bridges-2 | Bridges-2: https://www.psc.edu/resources/software/intel-vtune | Bridges-2: 2023.2.0 | |||||||||||||
intelcuda | Faster | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2020B | |||||||||||||
intelmpi | Bridges-2 | Intel MPI Libriaries. This module loads the Intel MPI implementation along with the Intel Compilers. | Intel MPI Library focuses on enabling applications to perform better on Intel architecture-based clusters. It enables applications to gain faster communication performance on Intel Xeon Phi coprocessors and Intel Xeon processors. | High Performance Computing (Hpc), Message Passing Interface (Mpi) Library, Optimized For Intel Architecture | Library | Hpc, Mpi Library, Intel Architecture | Engineering & Technology | Bridges-2: https://www.psc.edu/resources/software/intelmpi | Bridges-2: 20.4-Intel20.4, 2021.3.0-Intel2021.3.0, ... | Development Tools | ||||||
interproscan | Anvil, Faster | Interproscan is the software package that allows sequences to be scanned against InterPro's member database signatures. | InterProScan is a software tool that allows the functional analysis of protein sequences by classifying them into families and predicting domains and important sites. It combines different protein signature recognition methods in one resource. | Protein Sequence Analysis, Functional Classification, Domain Prediction, Signature Recognition | Bioinformatics Tool | Proteomics | Bioinformatics | Bioinformatics, Proteomics, Sequence Analysis, Functional Annotation | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/interproscan Faster: https://hprc.tamu.edu/software/faster/ |
Anvil: 5.54_87.0, 5.61-93.0 Faster: 5.52-86.0 |
Annotation Tool | ||||
intltool | Aces, Faster | intltool is a set of tools to centralize translation of many different file formats using GNU gettext-compatible PO files. Description Source: https://freedesktop.org/wiki/Software/intltool/ |
Intltool is a set of tools to centralize translation of many different file formats using a single language-styled file. | 1. Parsing and merging of existing translations. 2. Extraction of translatable strings from source code. 3. Generation of output files in different formats. | https://code.launchpad.net/intltool | Localization Tool | Localization, Translation, Internationalization | https://freedesktop.org/wiki/Software/intltool/ | Computer & Information Sciences | https://github.com/Distrotech/intltool/blob/master/README https://github.com/Distrotech/intltool/blob/master/doc/I18N-HOWTO |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.51.0 Faster: 0.51.0 |
Tools | |||
iomkl | Faster | IOMKL is a high-performance Mathematical Kernel Library (MKL) for Intel's Math Kernel Library developed for modern Intel CPUs. It is optimized for various mathematical operations and linear algebra computations. | Optimized For Modern Intel Cpus, High-Performance Mathematical Operations, Efficient Linear Algebra Computations | Library | Math Kernel Library, High-Performance Computing, Linear Algebra, Mathematical Operations | Mathematics | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2021A, 2022.00 | Computational Software | |||||||
iompi | Faster | IOMPI (Integrated Operator Methods Package Interface) is a software framework designed to facilitate the development and implementation of operator-based numerical methods for solving partial differential equations (PDEs) in computational physics and engineering. | 1. Provides a comprehensive set of tools for efficiently solving linear and nonlinear PDEs.\r 2. Supports a variety of numerical methods, such as finite element methods (FEM), finite difference methods (FDM), and spectral methods.\r 3. Offers support for parallel computing and can leverage high-performance computing (HPC) resources.\r 4. Includes pre-built solvers for common PDEs and allows users to implement custom solvers.\r 5. Enables easy integration with existing simulation codes and software packages. |
Library | Computational Physics | Applied Mathematics | Computational Software, Numerical Methods, Partial Differential Equations, Scientific Computing | Physical Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 2020B, 2021A, 2022.00 | Simulation Software | |||||
ior | Delta, Expanse | ior is a versatile software tool for analyzing and optimizing input/output (I/O) performance in high-performance computing (HPC) systems. It is designed to assess and improve the efficiency of data transfer operations in parallel computing environments. | I/O performance analysis, Parallel I/O optimization, Benchmarking, Profiling | Utility Software | High-Performance Computing | Computer Science | High-Performance Computing, Parallel Computing, I/O Optimization | Computer Science | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Delta: 3.3.0 Expanse: C3Prdsv, C5Wdybp, Fbtdgli, ... |
Performance Analysis Tool | |||||
iperf3 | Delta | iperf3 is a tool for actively measuring the maximum achievable bandwidth on IP networks. It supports various parameters to customize the testing process and is widely used for network performance testing and tuning. | 1. Measures TCP, UDP, and SCTP bandwidth performance\r 2. Supports IPv4 and IPv6\r 3. Option for bidirectional testing\r 4. Customizable testing parameters\r 5. Supports client-server architecture\r 6. Real-time measurements and statistics |
Tool | Network Testing, Bandwidth Measurement, Network Performance | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 3.6 | Network Testing | |||||||
ipmitool | Ookami | ipmitool is a utility for managing and configuring devices that support the Intelligent Platform Management Interface. IPMI is an open standard for monitoring, logging, recovery, inventory, and control of hardware that is implemented independent of the main CPU, BIOS, and OS. Description Source: https://github.com/ipmitool/ipmitool |
ipmitool is an open-source utility for managing and configuring devices that support the Intelligent Platform Management Interface (IPMI) specification. It allows users to interact with IPMI-enabled devices to retrieve information, perform system management tasks, and monitor hardware sensors remotely. | Retrieve System Information Remotely, Configure & Manage Ipmi-Enabled Devices, Monitor Hardware Sensors & Power Usage, Reset Or Power Cycle Systems Remotely, Execute Pre-Defined Commands On Remote Machines | https://www.mankier.com/1/ipmitool | Utility | System Management, Hardware Monitoring, Remote Administration, Open Source | https://github.com/ipmitool/ipmitool | Engineering & Technology | https://www.mankier.com/1/ipmitool#Examples | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 1.8.18 | System Management | |||
ipython | Aces, Faster | IPython is BSD-licensed, open-source software that is developed as a set of Subprojects under the ipython Github organization. These Subprojects are all part of the larger Project Jupyter umbrella. For further information about project governance, sponsorship and development, please see the Project page on Jupyter’s website. Description Source: https://ipython.org/project.html |
IPython is a powerful interactive command shell that provides a robust and flexible environment for interactive computing. It offers features such as easy-to-use, high-performance tools for parallel computing, data visualization, and data analysis. | Interactive Python Shell With Enhancements, Support For Data Visualization & Data Analysis, Parallel Computing Capabilities, Rich Media Integration, Integration With Other Programming Languages | https://ipython.readthedocs.io/en/stable/ | Development Tools | Software Engineering, Systems, & Development | Computer Science | Command Shell, Interactive Computing, Data Visualization, Parallel Computing, Data Analysis | https://ipython.org/ | Computer & Information Sciences | https://ipython.readthedocs.io/en/stable/interactive/tutorial.html | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 7.26.0, 8.5.0, 8.14.0 Faster: 7.15.0-Python-3.8.2, 7.18.1, 7.26.0, 8.5.0 |
Interpreter | |
iq-tree | Expanse | IQ-TREE is a fast and effective software for phylogenomic inference. It implements a variety of models for DNA and protein sequences, including substitution models, rate heterogeneity, and mixture models. IQ-TREE uses maximum likelihood estimation to construct phylogenetic trees, and offers ultrafast bootstrap approximation to assess the tree accuracy. | Phylogenomic Inference, Substitution Models, Ultrafast Bootstrap Approximation, Maximum Likelihood Estimation | Phylogenetic Tree Construction Tool | Phylogenetics | Systematics & Population Biology | Phylogenetics, Bioinformatics, Computational Biology, Phylogenomic Analysis | Biological Sciences | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Lvmeedg-Omp | Bioinformatics Software | |||||
iqtree | Anvil | IQ-TREE is an efficient phylogenomic software by maximum likelihood. | Anvil: https://www.rcac.purdue.edu/software/iqtree | Anvil: 1.6.12, 2.1.2, 2.2.0_Beta, 2.2.2.2 | ||||||||||||
iqtree2 | Anvil | IQ-TREE is an efficient phylogenomic software by maximum likelihood. | Anvil: https://www.rcac.purdue.edu/software/iqtree2 | Anvil: 2.2.2.6, 2.2.2.9 | ||||||||||||
irods-icommands | Bridges-2 | iCommands, the default command line interface to iRODS. | Bridges-2: https://www.psc.edu/resources/software/irods-icommands | Bridges-2: 4.3.0 | ||||||||||||
isa-l | Aces, Faster | The Intel® Intelligent Storage Acceleration Library (Intel® ISA-L) provides tools to minimize disk space use and maximize storage throughput, security, and resilience. Learn about its optimized functions for RAID, erasure code, cyclic redundancy check (CRC) functions, cryptographic hash, encryption, and compression. Description Source: https://www.intel.com/content/www/us/en/developer/tools/isa-l/overview.html |
ISA-L (Intel Storage Acceleration Library) is a collection of optimized low-level functions used in storage applications. It is specifically designed to offer high-performance data movement and protection functions for storage and data processing workloads, leveraging Intel hardware capabilities. | Optimized Low-Level Functions, High-Performance Data Movement, Data Protection Functions, Leverages Intel Hardware Capabilities | https://github.com/intel/isa-l/blob/master/doc/functions.md | Optimized Functions, Data Movement, Data Protection, Storage Applications | https://www.intel.com/content/www/us/en/developer/tools/isa-l/overview.html | Engineering & Technology | https://www.intel.com/content/www/us/en/developer/videos/intelligent-storage-acceleration-library.html https://github.com/intel/isa-l/tree/master/examples |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.30.0 Faster: 2.30.0 |
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isl | Aces, Faster | isl is a library for manipulating sets and relations of integer points bounded by linear constraints. | ISL (Integer Set Library) is a library for manipulating sets and maps of integer points bounded by linear constraints. It provides functions for computing the integer points in a set or projection of a set represented as unions of polyhedra, as wells as their images under affine transformations. | - Manipulating sets and maps of integer points\r - Computing integer points in a set\r - Intersection and union operations\r - Projection of a set\r - Affine transformations |
Library | Applied Computer Science | Computer Science | Library, Integer Points, Linear Constraints | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.26 Faster: 0.26 |
Computational Software | ||||
ismapper | Anvil | ISMapper searches for IS positions in sequence data using paired end Illumina short reads, an IS query/queries of interest and a reference genome. ISMapper reports the IS positions it has found in each isolate, relative to the provided reference genome. | Ismapper is a software for isomiR identification and differential expression analysis from small RNA-seq data. It is designed to accurately map and quantify isomiRs, which are isoforms of microRNAs resulting from alternative precursor processing and post-transcriptional modifications. | Accurate Mapping & Quantification Of Isomirs, Identification Of Differentially Expressed Isomirs, Analysis Of Small RNA-Seq Data, Visualization Of Isomir Expression Patterns | Analysis Tool | Bioinformatics, Computational Biology, Small RNA-Seq, Mirna Analysis | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/ismapper | Anvil: 2.0.2 | Bioinformatics Tools | ||||||
isoquant | Anvil | IsoQuant is a tool for the genome-based analysis of long RNA reads, such as PacBio or Oxford Nanopores. | Isoquant is a software tool used in economics to analyze production processes and determine the optimal combination of inputs to produce a given level of output. It is commonly used to study the trade-offs between factors of production such as labor and capital in maximizing output. | 1. Production analysis: Helps in determining the most efficient input combinations for a given level of output. 2. Isoquant mapping: Visualizes the various combinations of inputs that yield the same level of output. 3. Cost minimization: Assists in minimizing production costs while maximizing output. 4. Input substitution: Evaluates the impact of substituting one input for another on production efficiency. | Productivity Software | Production Analysis | Economics | Production Analysis, Input-Output Relationships, Economics | Social Sciences | Anvil: https://www.rcac.purdue.edu/software/isoquant | Anvil: 3.1.2 | Economic Modeling Tool | ||||
isoseq3 | Anvil | Anvil: https://www.rcac.purdue.edu/software/isoseq3 | Anvil: 3.4.0, 3.7.0, 3.8.2 | |||||||||||||
itac | Kyric, Stampede3 | The Intel® Trace Analyzer and Collector profiles and analyzes MPI applications to help focus your optimization efforts. Description Source: https://www.intel.com/content/www/us/en/developer/tools/oneapi/trace-analyzer.html#gs.4oj2fp |
Intel Trace Analyzer and Collector (ITAC) is a performance analysis tool designed for parallel applications. It provides in-depth performance data to help developers optimize the performance of their parallel code. | ITAC offers features such as tracing and profiling of parallel applications, identifying performance bottlenecks, visualizing application performance data, analyzing communication patterns, and providing detailed reports on the performance metrics. | https://www.intel.com/content/www/us/en/docs/trace-analyzer-collector/user-guide-reference/2021-10/overview.html | Compiler | Performance Analysis, Parallel Applications, Optimization | https://www.intel.com/content/www/us/en/developer/tools/oneapi/trace-analyzer.html | Computer & Information Sciences | https://www.intel.com/content/www/us/en/docs/trace-analyzer-collector/get-started-guide/2021-10/overview.html https://www.intel.com/content/www/us/en/docs/vtune-profiler/tutorial-vtune-itac-mpi-openmp/2020/overview.html https://www.intel.com/content/www/us/en/docs/trace-analyzer-collector/tutorial-correctness-checking/9-1-update-2/overview-001.html |
Stampede3: https://tacc.utexas.edu/use-tacc/software-list/ | Kyric: Latest, 2021.1.1 Stampede-3: 21.9, 22.0 |
Performance Analysis Tool | |||
itk | Aces, Faster | ITK is an open-source, cross-platform library that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions. Description Source: https://itk.org/ |
The Insight Segmentation and Registration Toolkit (ITK) is an open-source, cross-platform library that provides advanced image processing algorithms for registering and segmenting multidimensional scientific images. | ITK offers a wide range of tools for image analysis, including image filtering, segmentation, registration, and visualization. It provides support for N-dimensional images and is designed to be extensible, facilitating the integration of new algorithms. | https://docs.itk.org/en/latest/ | Image Analysis | Biomedical Imaging | Medical & Health Sciences | Image Processing, Medical Imaging, Scientific Images | https://itk.org/ | Engineering & Technology | https://examples.itk.org// https://github.com/InsightSoftwareConsortium/ScientificImageAnalysisVisualizationAndArtificialIntelligenceCourse https://itk.org/ItkSoftwareGuide.pdf |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.2.1 Faster: 5.2.1 |
Library | |
ivar | Anvil | Ivar is a computational package that contains functions broadly useful for viral amplicon-based sequencing. | Ivar is an open-source lightweight templating engine for Python, focused on simplicity and ease of use. | Ivar allows for easy template creation and usage, supports simple placeholders for data replacement, and offers basic control structures like conditionals and loops. | Library | Python Library, Templating Engine, Open-Source | Computer & Information Sciences | Anvil: https://www.rcac.purdue.edu/software/ivar | Anvil: 1.3.1, 1.4.2 | Development | ||||||
jags | Expanse, Faster | JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. Description Source: https://mcmc-jags.sourceforge.io/ |
JAGS (Just Another Gibbs Sampler) is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation. It is similar to WinBUGS and provides a flexible environment for specifying complex statistical models. | 1. Bayesian hierarchical modeling\r 2. Markov Chain Monte Carlo (MCMC) simulation\r 3. Model specification\r 4. Posterior inference\r 5. Parameter estimation |
https://cran.r-project.org/web/packages/rjags/rjags.pdf | Statistical Modeling | Bayesian Statistics | Statistics & Probability | Bayesian Statistics, Hierarchical Modeling, Mcmc Simulation | https://mcmc-jags.sourceforge.io/ | Mathematics | https://www.sas.rochester.edu/psc/thestarlab/help/JAGS.pdf | Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Expanse: 4.3.0 Faster: 4.3.0 |
Statistical Analysis Software | |
jansson | Aces, Faster | Jansson is a C library for encoding, decoding and manipulating JSON data. Its main features and design principles are: * Simple and intuitive API and data model * Comprehensive documentation * No dependencies on other libraries * Full Unicode support (UTF-8) * Extensive test suite | Jansson is a C library for encoding, decoding, and manipulating JSON data. It is designed to be efficient, powerful, and easy to use for integrating JSON parsing and generation capabilities into C/C++ applications. | 1. Parsing and generation of JSON data.\r 2. Supports precise error reporting for debugging.\r 3. Extendable through custom memory allocation functions.\r 4. Provides a flexible API for manipulating JSON data structures.\r 5. High performance and low memory consumption. |
Data Processing | Json, C Library, Data Parsing, Data Manipulation | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.13.1 Faster: 2.13.1 |
Library | ||||||
jasper | Aces, Expanse, Faster | Jasper is an open-source JPEG image codec library that provides encoding and decoding functionality for JPEG images. It is designed for high performance and is commonly used in applications that require image compression and decompression capabilities. | JasPer (JPEG-2000 Part-1 Suite) is an open-source software implementation of the JPEG-2000 Part-1 standard. It provides a complete set of tools for encoding and decoding JPEG-2000 streams, including color space conversion, wavelet transforms, quantization, and entropy coding. | 1. Support for encoding and decoding JPEG-2000 images\r 2. Color space conversion\r 3. Wavelet transforms\r 4. Quantization\r 5. Entropy coding |
https://jasper-software.github.io/jasper-manual/latest/html/index.html | Image Processing | Data Compression | Computer Science | Image Processing, Open-Source, Jpeg-2000 | https://www.ece.uvic.ca/~frodo/jasper/ | Computer & Information Sciences | https://jasper-software.github.io/jasper-manual/latest/html/lib.html#lib_intro https://jasper-software.github.io/jasper-manual/latest/html/lib_init.html#init_setup_example_1 https://jasper-software.github.io/jasper-manual/latest/html/apps.html#app_intro |
Aces: https://hprc.tamu.edu/software/aces/ Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.0.24, 2.0.28, 2.0.33, 4.0.0 Expanse: 2.0.16 Faster: 1.900.1, 2.0.14, 2.0.24, 2.0.28, 2.0.33, 4.0.0 |
Library | |
java | Aces, Faster | Java is a programming language and computing platform first released by Sun Microsystems in 1995. It has evolved from humble beginnings to power a large share of today’s digital world, by providing the reliable platform upon which many services and applications are built. New, innovative products and digital services designed for the future continue to rely on Java, as well. Description Source: https://www.java.com/en/download/help/whatis_java.html |
Java is a widely-used programming language and computing platform that is designed to be fast, secure, and reliable. It is commonly used for building mobile applications, web applications, enterprise applications, and more. | Java is platform-independent, object-oriented, and has a large standard library. It supports multithreading, garbage collection, and exception handling. Java applications are typically compiled to bytecode that can run on any Java virtual machine (JVM). | https://docs.oracle.com/en/java/javase/22/docs/api/index.html | Compiler | Programming Language, Computing Platform | https://www.oracle.com/java/ | Computer & Information Sciences | https://docs.oracle.com/javase/tutorial/ https://docs.oracle.com/javase/tutorial/reallybigindex.html https://www.w3schools.com/java/ https://www.tutorialspoint.com/java/index.htm https://www.codecademy.com/learn/learn-java |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.8.0_371, 11.0.16, 11.0.18, 17.0.6 Faster: 1.8.0_281, 1.8.0_292-Openjdk, 11.0.2, 13.0.2, 15.0.1, 17.0.2 |
Programming Language | |||
jax | Aces, Faster | JAX is Autograd and XLA, brought together for high-performance numerical computing, including large-scale machine learning research. Description Source: https://github.com/google/jax |
JAX is an open-source software library for high-performance machine learning research, particularly for automatic differentiation, and numerical and scientific computing. | JAX provides a functional framework that extends NumPy and enables GPU/TPU acceleration, automatic differentiation for Python and NumPy functions, custom vectorizable NumPy functions, composable transformations, and efficient gradient computation. | https://jax.readthedocs.io/en/latest/ | Machine Learning | Artificial Intelligence & Intelligent Systems | Machine Learning, Numerical Computing, Scientific Computing | https://github.com/google/jax | Computer & Information Sciences | https://jax.readthedocs.io/en/latest/notebooks/quickstart.html https://jax.readthedocs.io/en/latest/jax-101/index.html https://jax.readthedocs.io/en/latest/advanced_guide.html |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.2.20, 0.3.25-Cuda-11.7.0, 0.3.25, 0.4.4-Cuda-11.8.0, 0.4.4 Faster: 0.2.19, 0.2.24-Cuda-11.3.1, 0.2.24, 0.3.9-Cuda-11.3.1, 0.3.9, 0.3.23-Cuda-11.7.0 |
Library | ||
jbigkit | Aces, Faster | JBIG-KIT is a software implementation of the JBIG1 data compression standard (ITU-T T.82), which was designed for bi-level image data, such as scanned documents. This library is available in portable C code. It is widely used in fax products, printer firmware, printer drivers, document management systems and imaging software. Description Source: https://www.cl.cam.ac.uk/~mgk25/jbigkit/ |
https://github.com/nu774/jbigkit | https://www.cl.cam.ac.uk/~mgk25/jbigkit/ | https://github.com/nu774/jbigkit/tree/master/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.1 Faster: 2.1 |
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jcvi | Anvil | Jcvi is a collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics. | J. Craig Venter Institute (JCVI) software tools for bioinformatics analysis and computational biology. | JCVI offers a suite of bioinformatics tools for analyzing biological data, including sequence alignment, assembly, visualization, and annotation. These tools are designed to assist researchers in genomics, metagenomics, transcriptomics, and other areas of computational biology. | Analysis Tools | Genomics | Bioinformatics | Bioinformatics, Computational Biology | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/jcvi | Anvil: 1.2.7, 1.3.1 | Bioinformatics Tools | ||||
jdftx | Faster | JDFTx is a plane-wave density-functional theory (DFT) code designed to be as easy to develop with as it is easy to use. JDFTx is written using highly-templated and object oriented C++11 code in order to express all the physics in the DFT++ algeraic framework [13], while simultaneously maintaining a small memory footprint and supporting a range of hardware architectures (such as GPUs using CUDA) without requiring hand-optimized implementations for each architecture. Description Source: https://jdftx.org/ |
JDFTx is a computational package for joint density-functional theory (JDFT) calculations. It enables electronic structure calculations for materials using the JDFT formalism, offering a versatile tool for a wide range of research applications. | Performs Density-Functional Theory Calculations, Supports Joint Density-Functional Theory (Jdft), Allows For Electronic Structure Analysis Of Materials, Includes Features For Simulating Various Physical Properties | https://jdftx.org/DevGuide.html | Simulation Software | Computational Software, Electronic Structure Calculations, Materials Science | https://jdftx.org/ | Physical Sciences | https://jdftx.org/Tutorials.html | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.7.0-Cuda-12.2.0, 1.7.0 | Scientific Software | |||
jdk | Darwin | JDK (Java Development Kit) is a software development environment used for developing Java applications. It includes a Java Runtime Environment (JRE), an interpreter/loader (Java), a compiler (javac), an archiver (jar), a documentation generator (Javadoc), and some other tools needed in Java development. | Java Development, Compilation, Documentation Generation, Runtime Environment, Archiving | Compiler | Development Kit, Software Development, Java | Computer & Information Sciences | Development Tools | |||||||||
jellyfish | Expanse | Jellyfish is a fast and memory-efficient software for counting k-mers in DNA sequences, which are commonly used in genome analysis and sequence assembly. It provides algorithms for k-mer counting, storage, and querying to extract valuable insights from biological data. | Jellyfish is a tool for fast, memory-efficient counting of k-mers in DNA sequences. It has the capability to efficiently store and query k-mer counts in large sequencing datasets. | 1. Counting k-mers in DNA sequences\r 2. Memory-efficient data storage\r 3. Fast querying of k-mer counts\r 4. Support for large sequencing datasets |
https://github.com/gmarcais/Jellyfish/tree/master/doc | Bioinformatics Tool | K-Mer Counting, DNA Sequences, Sequence Analysis | https://www.genome.umd.edu/jellyfish.html | Biological Sciences | https://github.com/gmarcais/Jellyfish/tree/master/examples https://github.com/gmarcais/Jellyfish/tree/master#usage |
Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules | Expanse: Xvw2Ec7 | Computational Biology | |||
jemalloc | Aces, Faster | jemalloc is a general purpose malloc(3) implementation that emphasizes fragmentation avoidance and scalable concurrency support. | jemalloc is a general-purpose memory allocator implementation designed for high performance in multithreaded applications. It is widely used in the software industry to optimize memory allocation and improve overall performance of applications. | Efficient Memory Allocation & Deallocation, Optimized For Multithreaded Applications, Scalable & Customizable, Supports Advanced Memory Management Features | Memory Allocator | Memory Allocator, Performance Optimization, Multithreading | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 5.2.1 Faster: 5.2.1 |
Library | ||||||
jmol | Aces | Jmol: an open-source Java viewer for chemical structures in 3D with features for chemicals, crystals, materials and biomolecules | Jmol is an open-source Java viewer for chemical structures in 3D with features for visualization, analysis, and manipulation of molecular structures. | Jmol allows users to view 3D chemical structures, display crystal structures, visualize protein structures, animate molecules, and perform measurements and analysis on molecular structures. It supports a wide range of file formats for input and output, including CIF, PDB, XYZ, and more. Users can customize the display of molecules with various rendering options, color schemes, and labeling. | Modeling & Simulation | Chemical Sciences | Physical Chemistry, Inorganic & Nuclear Chemistry | Molecular Visualization, Molecular Analysis, Chemistry | Chemical Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 16.1.59-Java-1.8.0_371, 16.1.59 | Visualization | ||||
json-c | Aces, Faster, Kyric | JSON-C implements a reference counting object model that allows you to easily construct JSON objects in C, output them as JSON formatted strings and parse JSON formatted strings back into the C representation of JSON objects. It aims to conform to RFC 7159. Description Source: https://github.com/json-c/json-c/wiki |
Json-c is a C library for encoding, decoding, and manipulating JSON data. It provides functions for parsing JSON input, creating JSON output, manipulating JSON data structures, and validating JSON data. | Parsing Json Input, Creating Json Output, Manipulating Json Data Structures, Validating Json Data | https://json-c.github.io/json-c/json-c-0.17/doc/html/index.html | Data Processing | Software Engineering, Systems, & Development | Computer Science | C Library, Json Encoding, Json Decoding, Data Manipulation | https://github.com/json-c/json-c | Computer & Information Sciences | https://github.com/json-c/json-c/wiki/List-of-json-c-tutorials | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 0.16 Faster: 0.16 |
Library | |
jsoncpp | Aces, Faster | JsonCpp is a C++ library that allows manipulating JSON values, including serialization and deserialization to and from strings. It can also preserve existing comment in unserialization/serialization steps, making it a convenient format to store user input files. Description Source: https://github.com/open-source-parsers/jsoncpp |
JsonCpp is a C++ library that allows manipulating JSON data structures. It provides features for parsing, generating, and manipulating JSON data in C++ applications. | Parsing Json Data, Generating Json Data, Manipulating Json Data Structures, Support For C++ Applications | https://open-source-parsers.github.io/jsoncpp-docs/doxygen/index.html | Development Tools | C++, Json, Library, Data Manipulation | https://github.com/open-source-parsers/jsoncpp | Computer & Information Sciences | https://github.com/open-source-parsers/jsoncpp/wiki#code-example https://open-source-parsers.github.io/jsoncpp-docs/doxygen/index.html#_example https://github.com/open-source-parsers/jsoncpp/tree/master/example |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 1.9.4, 1.9.5 Faster: 1.9.3, 1.9.4, 1.9.5 |
Library | |||
judy | Faster | Judy is a C library that provides a collection of functions to efficiently manage data arrays to store and retrieve key/value pairs. | Some core features of Judy include high performance, memory efficiency, scalability with large data sets, support for dynamic arrays, and a simple API for easy integration. | Data Management | C Library, Data Management, Key/Value Pairs | Other Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 1.0.5 | Library | |||||||
julia | Aces, Anvil, Bridges-2, Darwin, Delta, Expanse, Faster, Ookami | Julia is a general purpose high-performance flexible programming language which can be used to write any application. It is well-suited for scientific and numerical computing. Description Source: https://julialang.org/ |
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and extensive mathematical function libraries. | Julia combines the high-level ease of use and flexibility of languages like Python and Matlab with the speed and performance of lower-level languages like C and Fortran. It offers a just-in-time compiler that generates optimized machine code using LLVM, making it highly efficient for numerical and scientific computing. Julia supports multiple dispatch, which allows functions to be defined with multiple methods with different argument types or numbers. It also has built-in package manager and a vast ecosystem of packages for various domains such as data science, machine learning, optimization, and more. | https://docs.julialang.org/en/v1/ | Compiler | Programming Language, Technical Computing, High-Performance Computing, Scientific Computing, Numerical Analysis | https://julialang.org/ | Computer & Information Sciences | https://juliaacademy.com/courses/ https://www.youtube.com/user/JuliaLanguage/playlists https://julialang.org/learning/tutorials/ https://julialang.org/learning/notebooks/ |
Aces: https://hprc.tamu.edu/software/aces/ Anvil: https://www.rcac.purdue.edu/software/julia Bridges-2: https://www.psc.edu/resources/software/julia Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules Faster: https://hprc.tamu.edu/software/faster/ Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Aces: 1.8.5-Linux-X86_64, 1.9.3-Linux-X86_64, 1.10.0-Musl-X86_64, 1.10.2-Linux-X86_64 Anvil: V2.4.2, 1.6.2 Bridges-2: 1.5.2 Delta: 1.9.0, 1.10.2 Expanse: Olutp43 Faster: 1.6.5-Linux-X86_64, 1.7.0-Linux-X86_64, 1.7.1-Linux-X86_64, 1.7.2-Linux-X86_64, 1.8.0-Linux-X86_64, 1.9.3-Linux-X86_64 Ookami: 1.8.3 |
Programming Language | |||
junit | Faster | JUnit is a popular open-source unit testing framework for Java programming language. It is widely used by developers to write and run repeatable automated tests to ensure the correctness of their code. | Supports Writing & Running Automated Tests In Java, Provides Annotations For Test Methods, Includes Assertion Methods For Test Results, Supports Test Fixtures To Set Up Initial Conditions, Generates Test Reports For Easy Result Analysis | Development Tool | Software Development | Software Engineering, Systems, & Development | Unit Testing, Java, Testing Framework | Computer & Information Sciences | Faster: https://hprc.tamu.edu/software/faster/ | Faster: 4.12-Java-1.8 | Software Testing Framework | |||||
jupyter | Anvil, Jetstream, Ookami | JupyterLab is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. | Jupyter is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It supports over 40 programming languages, including Python, R, and Julia, and is widely used in data science, scientific computing, and machine learning projects. | Interactive Computing, Data Visualization, Collaborative Notebooks, Support For Multiple Programming Languages | https://docs.jupyter.org/en/latest/ | Web Application | Data Science, Scientific Computing, Machine Learning | https://jupyter.org/ | Computer & Information Sciences | https://docs.jupyter.org/en/latest/use/using.html https://docs.jupyter.org/en/latest/start/index.html |
Anvil: https://www.rcac.purdue.edu/software/jupyter Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami |
Anvil: 2.0.0 Ookami: Latest |
Computational Notebook | |||
jupyter-notebook | Ookami | Ookami: https://www.stonybrook.edu/commcms/ookami/support/faq/software_on_ookami | Ookami: 7.0.6 | |||||||||||||
jupyter-server | Aces | The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter notebook, JupyterLab, and Voila. | Jupyter server is a flexible and extensible tool that allows users to run interactive computational environments in various programming languages. It provides a web-based interface for running Jupyter notebooks, code, and data analysis. | Web-Based Interface, Interactive Computational Environments, Support For Multiple Programming Languages | Compiler | Interactive Computing, Web-Based Interface, Notebooks | Computer & Information Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 2.7.0, 2.7.2 | Computational Software | ||||||
jupyterhub | Jetstream | JupyterHub brings the power of notebooks to groups of users. It gives users access to computational environments and resources without burdening the users with installation and maintenance tasks. | JupyterHub brings the power of Jupyter Notebooks to groups of users. It allows multiple users to access Jupyter Notebooks through a browser, providing a collaborative and interactive environment for data science, scientific computing, and other computational tasks. | Multi-User Jupyter Notebook Server, Browser-Based Interface, Support For Multiple Languages Including Python, R, & Julia, Scalability For Large Groups Of Users, Customizable User Environments, Integration With Authentication Services Like Oauth & Ldap | https://jupyterhub.readthedocs.io/en/stable/ | Collaborative Tool | Data Science | Informatics, Analytics & Information Science | Data Science, Collaborative Computing, Notebook Environment, Interactive Computing | https://jupyter.org/hub | Computer & Information Sciences | https://jupyterhub.readthedocs.io/en/stable/tutorial/index.html https://jupyterhub.readthedocs.io/en/stable/howto/index.html https://github.com/jupyterhub/jupyterhub-tutorial |
Data Science Tools | |||
jupyterlab | Aces, Jetstream | JupyterLab is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. | JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. It offers a flexible and powerful user interface to work with data, code, and visualization in a seamless manner. | Web-Based Interface For Interactive Computing, Support For Jupyter Notebooks, Text Editors, Terminals, & Custom Components, Integration With Data Visualization Libraries & Tools, Ability To Work With Multiple Programming Languages Like Python, R, & Julia, Customizable User Interface With Drag-&-Drop Features, Interactive Widgets For Data Exploration & Visualization | https://jupyterlab.readthedocs.io/en/stable/user/index.html | Data Science Tool | Interactive Computing, Data Visualization, Jupyter Notebooks, Web-Based Interface, Code Editing | https://github.com/jupyterlab/jupyterlab | Computer & Information Sciences | https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html https://www.youtube.com/watch?v=7wfPqAyYADY |
Aces: https://hprc.tamu.edu/software/aces/ | Aces: 4.0.3 | Integrated Development Environment (Ide) | |||
jupyterlmod | Aces | Jupyter interactive notebook server extension that allows users to interact with environment modules before launching kernels. The extension uses Lmod's Python interface to accomplish module-related tasks like loading, unloading, saving collections, etc. | jupyterlmod is an extension for Jupyter Notebooks that allows users to interact with Lmod, the Environment Modules System, directly within the Jupyter environment. It enables users to manage software environments, load and unload modules, and handle environment variables conveniently within Jupyter Notebook. | Integration Of Lmod With Jupyter Notebooks, Software Environment Management, Module Loading & Unloading, Environment Variable Handling | Extension | Jupyter Notebook, Environment Modules, Software Environment Management | Other Natural Sciences | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 4.0.3 | Environment Management | ||||||
jupyternotebook | Aces | The Jupyter Notebook is the original web application for creating and sharing computational documents. It offers a simple, streamlined, document-centric experience. | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 7.0.3 | ||||||||||||
kahip | Aces, Faster | KaHIP - Karlsruhe High Quality Partitioning - is a family of graph partitioning programs. It includes KaFFPa (Karlsruhe Fast Flow Partitioner), which is a multilevel graph partitioning algorithm, in its variants Strong, Eco and Fast, KaFFPaE (KaFFPaEvolutionary) which is a parallel evolutionary algorithm that uses KaFFPa to provide combine and mutation operations, as well as KaBaPE which extends the evolutionary algorithm. Moreover, specialized techniques are included to partition road networks (Buffoon), to output a vertex separator from a given partition or techniques geared towards efficient partitioning of social networks. Description Source: https://kahip.github.io/ |
KaHIP (Karlsruhe High Quality Partitioning) is a family of graph partitioning programs that aims to efficiently compute high-quality graph partitions. It provides several partitioning algorithms to balance computational load and minimize communication overhead. KaHIP is suitable for large-scale parallel applications and is widely used in the field of high-performance computing. | Efficient Computation Of High-Quality Graph Partitions, Multiple Partitioning Algorithms, Optimization For Load Balancing & Communication Reduction, Suitable For Large-Scale Parallel Applications | https://github.com/KaHIP/KaHIP | Utility | Computer Science | Graph Partitioning, High-Performance Computing, Parallel Computing | https://kahip.github.io/ | Computer & Information Sciences | https://github.com/KaHIP/KaHIP/tree/master/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.14, 3.16 Faster: 3.14 |
Algorithm | ||
kaiju | Anvil | Kaiju is a tool for fast taxonomic classification of metagenomic sequencing reads using a protein reference database. | Kaiju is a program for the taxonomic classification of high-throughput sequencing reads. It assigns taxonomic labels to short DNA sequences with near-perfect accuracy. Kaiju is based on the Burrows-Wheeler transform (BWT) and the FM-index. It has been designed to analyze sequencing reads generated by high-throughput sequencing technologies, such as Illumina, Pacific Biosciences, and Ion Torrent. | Taxonomic Classification Of DNA Sequences, High Accuracy In Assigning Taxonomic Labels, Utilizes Burrows-Wheeler Transform & Fm-Index, Designed For High-Throughput Sequencing Reads | Sequence Analysis Tool | Bioinformatics | Biological Sciences | Bioinformatics, Computational Biology, Genomics, Sequencing Data | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/kaiju | Anvil: 1.8.2 | Bioinformatics Tool | ||||
kakscalculator2 | Anvil | kakscalculator2 is a toolkit of incorporating gamma series methods and sliding window strategies. | kakscalculator2 is a software tool designed for performing advanced mathematical calculations and computations. It provides a user-friendly interface for solving complex mathematical problems efficiently. | 1. Advanced mathematical calculations\r 2. User-friendly interface\r 3. Efficient computation of complex problems\r 4. Mathematical modeling capabilities |
Tool | Mathematics, Software, Computation | Mathematics | Anvil: https://www.rcac.purdue.edu/software/kakscalculator2 | Anvil: 2.0.1 | Mathematical Calculation | ||||||
kalign | Aces, Faster | Kalign is a fast multiple sequence alignment program for biological sequences. Description Source: https://github.com/TimoLassmann/kalign |
Kalign is a fast and accurate multiple sequence alignment algorithm that utilizes the Wu-Manber approximate string matching algorithm to efficiently align large sets of sequences. It is commonly used in bioinformatics for aligning DNA, RNA, and protein sequences. | Fast & Accurate Multiple Sequence Alignment, Utilizes The Wu-Manber Approximate String Matching Algorithm, Suitable For Aligning Large Sets Of Sequences, Supports DNA, RNA, & Protein Sequences | https://github.com/TimoLassmann/kalign | Bioinformatics Tool | Bioinformatics, Sequence Alignment, DNA, RNA, Protein, Wu-Manber Algorithm | https://github.com/TimoLassmann/kalign/blob/main/doc/paper/kalign3.org | Biological Sciences | https://github.com/TimoLassmann/kalign#examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 3.3.1, 3.3.5, 3.4.0 Faster: 3.3.1 |
Algorithm | |||
kallisto | Anvil, Expanse | Kallisto is a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. | kallisto is a program for quantifying abundances of transcripts from RNA-Seq data, using pseudoalignment to quickly determine compatibility of reads with targets, allowing rapid transcript quantification. | Efficient & Ultrafast RNA-Seq Quantification, Pseudoalignment-Based Approach, Accurate & Reliable Transcript Quantification, Compatibility With Standard RNA-Seq Analysis Pipelines, Multiple Output Formats For Downstream Analysis | Bioinformatics Tool | Transcriptomics | Bioinformatics | RNA-Seq, Transcriptomics, Bioinformatics, Gene Expression Analysis, Computational Biology | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/kallisto Expanse: https://www.sdsc.edu/support/user_guides/expanse.html#modules |
Anvil: 0.46.2, 0.48.0 Expanse: Bdaqnwj |
Quantification Tool | ||||
kblas-gpu | Aces | KAUST BLAS (KBLAS) is a high performance CUDA library implementing a subset of BLAS as well as Linear Algebra PACKage (LAPACK) routines on NVIDIA GPUs. | KBLAS is a GPU-accelerated linear algebra library for high-performance computing (HPC) applications. It provides optimized implementations of basic linear algebra subroutines (BLAS) and dense matrix operations for NVIDIA GPUs. | 1. Accelerated linear algebra operations on NVIDIA GPUs. 2. Optimized Basic Linear Algebra Subroutines (BLAS) for high-performance computing. 3. Dense matrix operations such as matrix-matrix multiplication, matrix-vector multiplication, etc. 4. Support for various data types and precision levels. 5. High-performance and parallel computation capabilities. | Computational Software | Linear Algebra, Gpu-Accelerated, Hpc, Parallel Computing | Engineering & Technology | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 20231024-Cuda-11.8.0 | Numerical Library | ||||||
kbproto | Delta | The kbproto package provides the core XKB protocol and extension definitions for usage with X11 protocol libraries. | 1. Provides XKB protocol and extension definitions. 2. Allows for usage with X11 protocol libraries. 3. Defines keyboard properties and types for X Window System. | Protocol | Computer Science | Computer Science | X11 Protocol, Keyboard Properties | Computer & Information Sciences | Delta: https://docs.ncsa.illinois.edu/systems/delta/en/latest/user_guide/software.html | Delta: 1.0.7 | Library | |||||
kcachegrind | Darwin | KCacheGrind is a visualisation tool that allows to profile data and identify performance bottlenecks in software applications. It is commonly used for analyzing profiling data generated by Cachegrind and Callgrind. | Visualize Profiling Data, Identify Performance Bottlenecks, Interact With Call Graphs & Call Trees, View Cache Utilization & Branch Prediction | Visualization Tool | Performance Analysis, Software Profiling, Software Visualization | Computer & Information Sciences | Development Tools | |||||||||
kentutils | Anvil | Kentutils: UCSC command line bioinformatic utilities. | kentutils is a collection of utilities provided by the UCSC Genome Browser that allow for the manipulation and analysis of genomic data. These tools are particularly useful for researchers working with genomics data and looking to perform various operations on genome sequences. | 1. Utilities for manipulating genomic data.\r 2. Tools for analyzing genome sequences.\r 3. Support for various file formats commonly used in genomics. |
Bioinformatics Tools | Genomics, Computational Biology | Bioinformatics | Genomics, Genome Browser, Utilities | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/kentutils | Anvil: 302.1.0 | Utility | ||||
keras | Aces, Faster | Keras is a deep learning API written in Python and capable of running on top of either JAX, TensorFlow, or PyTorch. Description Source: https://keras.io/about/ |
Keras is an open-source neural network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML. Designed with user-friendliness and modularity as its guiding principles, Keras is known for its ease of use and flexibility, allowing users to experiment with deep neural networks. | 1. User-friendly API\r 2. Modular and extensible\r 3. Supports both convolutional networks and recurrent networks, as well as combinations of the two\r 4. Runs seamlessly on CPU and GPU |
https://keras.io/api/ | Library | Machine Learning | Artificial Intelligence & Intelligent Systems | Neural Networks, Deep Learning, Machine Learning | https://keras.io/ | Computer & Information Sciences | https://www.tensorflow.org/guide/keras https://keras.io/getting_started/intro_to_keras_for_engineers/ https://keras.io/examples/ |
Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.4.3-Tensorflow-2.5.0 Faster: 2.4.3 |
Neural Network Library | |
khmer | Anvil | Khmer is a tool for k-mer counting, filtering, and graph traversal FTW! | Khmer is a set of tools for working with DNA sequence data that is extremely efficient both in terms of speed and memory consumption. It is designed to pre-process sequencing data to reduce the memory requirements of de Bruijn graph based assemblers for metagenome data. The tools can be used for counting k-mers and finding k-mers that occur many times, trimming and error-trimming data, digital normalization of reads, and partitioning large data sets. | K-Mer Counting, Data Trimming & Error-Trimming, Digital Normalization Of Reads, Partitioning Large Data Sets | Bioinformatics Tool | Bioinformatics, Hpc Tools, Computational Software | Biological Sciences | Anvil: https://www.rcac.purdue.edu/software/khmer | Anvil: 3.0.0A3 | Research Tools | ||||||
kim-api | Aces, Faster | The Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API) defines a standard (the Portable Model Interface (PMI)) for how molecular simulators interface with interatomic models (also called potentials or force-fields). This allows a single computer implementation of a Portable Model (PM) to be used without modification within multiple simulator codes. A PM can include code and parameters all in one. Or, a PM can include just parameters and use a separate Model Driver (MD) library containing the code. Description Source: https://openkim.org/kim-api/ |
The Knowledgebase for Interatomic Models (KIM) Application Programming Interface (API) is an open framework for the development of interoperable atomistic and multiscale simulation codes. It provides a common interface for atomistic simulations and facilitates the incorporation and sharing of interatomic models. | 1. Standardizes the interface between atomistic simulation codes and interatomic potential models.\r 2. Enables the seamless integration of new potential models into existing simulation codes.\r 3. Facilitates the sharing and dissemination of interatomic models within the materials science community.\r 4. Supports multiple programming languages, including C/C++, Fortran, Python, and MATLAB. |
https://kim-api.readthedocs.io/en/latest/ | Application Programming Interface | Materials Simulation | Materials Science | Computational Software, Hpc Tools | https://openkim.org/kim-api/ | Physical Sciences | https://github.com/openkim/kim-api/tree/master/examples | Aces: https://hprc.tamu.edu/software/aces/ Faster: https://hprc.tamu.edu/software/faster/ |
Aces: 2.2.1, 2.3.0 Faster: 2.1.3, 2.2.1, 2.3.0 |
Simulation Tools | |
kineto | Aces | kineto is a CPU+GPU Profiling library that provides access to timeline traces and hardware performance counters. Description Source: https://github.com/pytorch/kineto |
Kineto is a software suite designed for analyzing and simulating the dynamics of mechanical systems. It provides tools for both kinematic and dynamic analysis of systems with rigid bodies, joints, and constraints. Kineto is particularly useful for studying the motion and forces in complex mechanical systems. | Kinematic Analysis Of Mechanical Systems, Dynamic Analysis Of Mechanical Systems, Simulation Of Rigid Body Motion With Joints & Constraints, Visualization Of Motion & Forces In Mechanical Systems | https://github.com/pytorch/kineto/blob/main/libkineto/README.md | Analysis Tool | Mechanical Engineering | Engineering & Technology | Mechanical Engineering, Simulation, Mechanical Systems, Kinematics, Dynamics | https://github.com/pytorch/kineto | Engineering & Technology | https://github.com/pytorch/kineto/tree/main/libkineto/sample_programs | Aces: https://hprc.tamu.edu/software/aces/ | Aces: 0.4.0 | Simulation | |
kissde | Anvil | kissDE is a R package, similar to DEseq, but which works on pairs of variants, and tests if a variant is enriched in one condition. | KISSDE (Kinetic Simulator of Synthetic Degradation and Expression) is a software tool for simulating the kinetics of gene expression and protein degradation in synthetic biological systems. It allows users to model the dynamics of gene expression and protein degradation processes to better understand and optimize synthetic genetic circuits. | Simulation Of Gene Expression Dynamics, Modeling Protein Degradation Kinetics, Optimization Of Synthetic Genetic Circuits, Analysis Of Synthetic Biological Systems | Bioinformatics Tool | Synthetic Biology, Systems Biology | Biological Sciences | Computational Biology, Bioinformatics | Biological Sciences | < |