Modules avx512: Difference between revisions

| align="center" | 0.11.1, 0.15.1, 0.16.0, 0.17.1, 1.0.0, 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: bgc implements Bayesian estimation of genomic clines to quantify introgression at many loci. Models are available for linked loci, genotype uncertainty and sequence errors. Models for genotype uncertainty and sequence error can be used to estimate genomic cline parameters from next-generation sequence data. Homepage: https://sites.google.com/site/bgcsoftware/ URL: https://sites.google.com/site/bgcsoftware/<br /><br /><br /></div>

| align="center" | 0.2.1, 0.2.2, 0.3.0, 0.4.1, 0.4.3, 0.5.3, 0.6.1

| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: FragGeneScan is an application for finding (fragmented) genes in short reads. Homepage: http://omics.informatics.indiana.edu/FragGeneScan/ Keyword:bio<br /><br /><br /></div>

| align="center" | 2.1, 2.3, 2.3.1

| <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 Compatible modules: python/3.10, python/3.10, python/3.10, python/3.10, python/3.11, python/3.11, python/3.11, python/3.11 Extensions: glfw-2.6.2<br /><br /><br /></div>

| Documentation: [[GROMACS]]<div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Modified GROMACS for small-angle scattering calculations (SAXS/WAXS/SANS). This is a GPU enabled build, containing both MPI and threadMPI builds. - CC-Wiki: GROMACS Homepage: https://cbjh.gitlab.io/gromacs-swaxs-docs/ URL: https://cbjh.gitlab.io/gromacs-swaxs-docs/ Keyword:chem<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 Keyword:math<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>