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Modules avx512: Difference between revisions
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| align="center" | [https://arrow.apache.org arrow] | | align="center" | [https://arrow.apache.org arrow] | ||
| align="center" | tools | | align="center" | tools | ||
| align="center" | 0.11.1, 0.15.1, 0.16.0, 0.17.1 | | align="center" | 0.11.1, 0.15.1, 0.16.0, 0.17.1, 2.0.0, 5.0.0, 7.0.0, 8.0.0, 9.0.0, 10.0.1, 11.0.0, 12.0.1, 13.0.0, 14.0.0, 14.0.1, 15.0.1, 16.1.0 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Apache Arrow is a cross-language development platform for in-memory data. Homepage: https://arrow.apache.org URL: https://arrow.apache.org Compatible modules: python/3.11, python/3.10 Keyword:tools<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Apache Arrow is a cross-language development platform for in-memory data. Homepage: https://arrow.apache.org URL: https://arrow.apache.org Compatible modules: python/3.11, python/3.10 Keyword:tools<br /><br /><br /></div> | ||
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| align="center" | [https://github.com/NVIDIA/gdrcopy gdrcopy] | | align="center" | [https://github.com/NVIDIA/gdrcopy gdrcopy] | ||
| align="center" | - | | align="center" | - | ||
| align="center" | 2.1, 2.3.1 | | align="center" | 2.1, 2.3, 2.3.1 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: A low-latency GPU memory copy library based on NVIDIA GPUDirect RDMA technology. Homepage: https://github.com/NVIDIA/gdrcopy URL: https://github.com/NVIDIA/gdrcopy<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: A low-latency GPU memory copy library based on NVIDIA GPUDirect RDMA technology. Homepage: https://github.com/NVIDIA/gdrcopy URL: https://github.com/NVIDIA/gdrcopy<br /><br /><br /></div> | ||
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| align="center" | - | | align="center" | - | ||
| align="center" | 3.3.2, 3.3.8 | | align="center" | 3.3.2, 3.3.8 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: GLFW is an Open Source, multi-platform library for OpenGL, OpenGL ES and Vulkan development on the desktop Homepage: https://www.glfw.org URL: https://www.glfw.org | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: GLFW is an Open Source, multi-platform library for OpenGL, OpenGL ES and Vulkan development on the desktop Homepage: https://www.glfw.org URL: https://www.glfw.org<br /><br /><br /></div> | ||
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| align="center" | [https://ccb.jhu.edu/software/glimmerhmm glimmerhmm] | | align="center" | [https://ccb.jhu.edu/software/glimmerhmm glimmerhmm] | ||
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| align="center" | tools | | align="center" | tools | ||
| align="center" | 0.3.1 | | align="center" | 0.3.1 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: This is GLOST, the Greedy Launcher Of Small Tasks. Homepage: https://github.com/cea-hpc/glost Keyword:tools<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: This is GLOST, the Greedy Launcher Of Small Tasks. Homepage: https://github.com/cea-hpc/glost URL: https://github.com/cea-hpc/glost Keyword:tools<br /><br /><br /></div> | ||
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| align="center" | [https://www.gnu.org/software/glpk/ glpk] | | align="center" | [https://www.gnu.org/software/glpk/ glpk] | ||
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| align="center" | vis | | align="center" | vis | ||
| align="center" | 5.99.0 | | align="center" | 5.99.0 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Grace is a WYSIWYG 2D plotting tool for X Windows System and Motif. Homepage | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Grace is a WYSIWYG 2D plotting tool for X Windows System and Motif. Homepage: http://freecode.com/projects/grace Keyword:vis<br /><br /><br /></div> | ||
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| align="center" | [http://grackle.readthedocs.io grackle] | | align="center" | [http://grackle.readthedocs.io grackle] | ||
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| align="center" | math | | align="center" | math | ||
| align="center" | 4.0.3, 5.1.0 | | align="center" | 4.0.3, 5.1.0 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: METIS is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes. Homepage: http://glaros.dtc.umn.edu/gkhome/metis/metis/overview Keyword:math<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: METIS is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes. Homepage: http://glaros.dtc.umn.edu/gkhome/metis/metis/overview URL: http://glaros.dtc.umn.edu/gkhome/metis/metis/overview Keyword:math<br /><br /><br /></div> | ||
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| align="center" | [http://glaros.dtc.umn.edu/gkhome/metis/metis/overview metis-64idx] | | align="center" | [http://glaros.dtc.umn.edu/gkhome/metis/metis/overview metis-64idx] | ||
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| align="center" | bio | | align="center" | bio | ||
| align="center" | 2.0.1 | | align="center" | 2.0.1 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Minimac3 is a lower memory and more computationally efficient implementation of the genotype imputation algorithms in minimac and minimac2. Minimac3 is designed to handle very large reference panels in a more computationally efficient way with no loss of accuracy. Homepage: http://genome.sph.umich.edu/wiki/Minimac3 Keyword:bio<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Minimac3 is a lower memory and more computationally efficient implementation of the genotype imputation algorithms in minimac and minimac2. Minimac3 is designed to handle very large reference panels in a more computationally efficient way with no loss of accuracy. Homepage: http://genome.sph.umich.edu/wiki/Minimac3 URL: http://genome.sph.umich.edu/wiki/Minimac3 Keyword:bio<br /><br /><br /></div> | ||
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| align="center" | [https://genome.sph.umich.edu/wiki/Minimac4 minimac4] | | align="center" | [https://genome.sph.umich.edu/wiki/Minimac4 minimac4] | ||
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| align="center" | bio | | align="center" | bio | ||
| align="center" | 3.23, 4.0.0beta2 | | align="center" | 3.23, 4.0.0beta2 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form. AMOS makes use of it. Homepage | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form. AMOS makes use of it. Homepage: http://mummer.sourceforge.net/ Keyword:bio<br /><br /><br /></div> | ||
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| align="center" | [https://graal.ens-lyon.fr/MUMPS/ mumps-metis] | | align="center" | [https://graal.ens-lyon.fr/MUMPS/ mumps-metis] | ||
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| align="center" | geo | | align="center" | geo | ||
| align="center" | 1.0 | | align="center" | 1.0 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: proj4-fortran is a f77 and f90 wrappers for proj4, a cartograohic projections library. Homepage: https://github.com/mhagdorn/proj4-fortran Keyword:geo<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: proj4-fortran is a f77 and f90 wrappers for proj4, a cartograohic projections library. Homepage: https://github.com/mhagdorn/proj4-fortran URL: https://github.com/mhagdorn/proj4-fortran Keyword:geo<br /><br /><br /></div> | ||
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| align="center" | [https://www.vicbioinformatics.com/software.prokka.shtml prokka] | | align="center" | [https://www.vicbioinformatics.com/software.prokka.shtml prokka] | ||
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| align="center" | [https://repast.github.io/ repasthpc] | | align="center" | [https://repast.github.io/ repasthpc] | ||
| align="center" | bio | | align="center" | bio | ||
| align="center" | 2.2.0, 2.3.0 | | align="center" | 2.0, 2.2.0, 2.3.0 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: The Repast Suite is a family of advanced, free, and open source agent-based modeling and simulation platforms that have collectively been under continuous development for over 15 years: Repast for High Performance Computing 2.2.0, released on 30 September 2016, is a lean and expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers. Homepage: https://repast.github.io/ URL: https://repast.github.io/ Keyword:bio<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: The Repast Suite is a family of advanced, free, and open source agent-based modeling and simulation platforms that have collectively been under continuous development for over 15 years: Repast for High Performance Computing 2.2.0, released on 30 September 2016, is a lean and expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers. Homepage: https://repast.github.io/ URL: https://repast.github.io/ Keyword:bio<br /><br /><br /></div> | ||
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| align="center" | - | | align="center" | - | ||
| align="center" | 6.0.1.5, 8.6.1.6 | | align="center" | 6.0.1.5, 8.6.1.6 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: NVIDIA TensorRT is a platform for high-performance deep learning inference Homepage: https://developer.nvidia.com/tensorrt URL: https://developer.nvidia.com/tensorrt Compatible modules: python/3.10, python/3.11<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: NVIDIA TensorRT is a platform for high-performance deep learning inference Homepage: https://developer.nvidia.com/tensorrt URL: https://developer.nvidia.com/tensorrt Compatible modules: python/3.8, python/3.9, python/3.10, python/3.11<br /><br /><br /></div> | ||
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| align="center" | [https://github.com/tesseract-ocr/tesseract tesseract] | | align="center" | [https://github.com/tesseract-ocr/tesseract tesseract] | ||