{"id":14286,"date":"2015-07-20T23:46:10","date_gmt":"2015-07-20T20:46:10","guid":{"rendered":"http:\/\/hgpu.org\/?p=14286"},"modified":"2015-07-20T23:46:10","modified_gmt":"2015-07-20T20:46:10","slug":"gromacs-high-performance-molecular-simulations-through-multi-level-parallelism-from-laptops-to-supercomputers","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=14286","title":{"rendered":"GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers"},"content":{"rendered":"<p>GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced parallelization algorithms. These work on every level; SIMD registers inside cores, multithreading, heterogeneous CPU-GPU acceleration, state-of-the-art 3D domain decomposition, and ensemble-level parallelization through built-in replica exchange and the separate Copernicus framework. The latest best-in-class compressed trajectory storage format is supported.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,66,89,90,3],"tags":[1787,658,1790,14,452,968,20,1650,1793,176,1543],"class_list":["post-14286","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-chemistry","category-nvidia-cuda","category-opencl","category-paper","tag-algorithms","tag-biomolecules","tag-chemistry","tag-cuda","tag-heterogeneous-systems","tag-molecular-simulation","tag-nvidia","tag-nvidia-geforce-gtx-980","tag-opencl","tag-package","tag-tesla-k40"],"views":3439,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14286","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14286"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/14286\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14286"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14286"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14286"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}