{"id":17425,"date":"2017-08-08T09:11:14","date_gmt":"2017-08-08T06:11:14","guid":{"rendered":"https:\/\/hgpu.org\/?p=17425"},"modified":"2017-08-08T09:11:14","modified_gmt":"2017-08-08T06:11:14","slug":"an-efficient-mpiopenmp-parallelization-of-the-hartree-fock-method-for-the-second-generation-of-intel-xeon-phi-processor","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=17425","title":{"rendered":"An efficient MPI\/OpenMP parallelization of the Hartree-Fock method for the second generation of Intel Xeon Phi processor"},"content":{"rendered":"<p>Modern OpenMP threading techniques are used to convert the MPI-only Hartree-Fock code in the GAMESS program to a hybrid MPI\/OpenMP algorithm. Two separate implementations that differ by the sharing or replication of key data structures among threads are considered, density and Fock matrices. All implementations are benchmarked on a super-computer of 3,000 Intel Xeon Phi processors. With 64 cores per processor, scaling numbers are reported on up to 192,000 cores. The hybrid MPI\/OpenMP implementation reduces the memory footprint by approximately 200 times compared to the legacy code. The MPI\/OpenMP code was shown to run up to six times faster than the original for a range of molecular system sizes.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Modern OpenMP threading techniques are used to convert the MPI-only Hartree-Fock code in the GAMESS program to a hybrid MPI\/OpenMP algorithm. Two separate implementations that differ by the sharing or replication of key data structures among threads are considered, density and Fock matrices. All implementations are benchmarked on a super-computer of 3,000 Intel Xeon Phi [&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":[36,66,11,3,12],"tags":[1787,451,1790,1782,1483,242,252,1783],"class_list":["post-17425","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-chemistry","category-computer-science","category-paper","category-physics","tag-algorithms","tag-benchmarking","tag-chemistry","tag-computer-science","tag-intel-xeon-phi","tag-mpi","tag-openmp","tag-physics"],"views":2848,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/17425","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=17425"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/17425\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=17425"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=17425"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=17425"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}