{"id":11116,"date":"2013-12-19T23:03:07","date_gmt":"2013-12-19T21:03:07","guid":{"rendered":"http:\/\/hgpu.org\/?p=11116"},"modified":"2013-12-19T23:03:07","modified_gmt":"2013-12-19T21:03:07","slug":"experiences-porting-a-molecular-dynamics-code-to-gpus-on-a-cray-xk7","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11116","title":{"rendered":"Experiences Porting a Molecular Dynamics Code to GPUs on a Cray XK7"},"content":{"rendered":"<p>GPU computing has rapidly gained popularity as a way to achieve higher performance of many scientific applications. In this paper we report on the experience of porting a hybrid MPI+OpenMP molecular dynamics code to a GPU enabled CrayXK7 to make a hybrid MPI+GPU code. The target machine, Indiana University&#8217;s Big Red II, consists of a mix of nodes equipped with two 16-core Abu Dhabi X86-64 processors, and nodes equipped with one AMD Interlagos X86-64 processor and one Nvidia Kepler K20 GPU board. The code, IUMD, is a Fortran program developed at Indiana University for modeling matter in compact stellar objects (white dwarf stars, neutron stars and supernovas). We compare experiences using CUDA and OpenACC.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>GPU computing has rapidly gained popularity as a way to achieve higher performance of many scientific applications. In this paper we report on the experience of porting a hybrid MPI+OpenMP molecular dynamics code to a GPU enabled CrayXK7 to make a hybrid MPI+GPU code. The target machine, Indiana University&#8217;s Big Red II, consists of a [&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":[89,3,12],"tags":[14,989,112,242,20,1321,1783,1390],"class_list":["post-11116","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-paper","category-physics","tag-cuda","tag-fortran","tag-molecular-dynamics","tag-mpi","tag-nvidia","tag-openacc","tag-physics","tag-tesla-k20"],"views":4812,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11116","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=11116"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11116\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11116"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11116"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11116"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}