{"id":2544,"date":"2011-01-20T11:01:27","date_gmt":"2011-01-20T11:01:27","guid":{"rendered":"http:\/\/hgpu.org\/?p=2544"},"modified":"2011-01-20T11:01:27","modified_gmt":"2011-01-20T11:01:27","slug":"direct-n-body-kernels-for-multicore-platforms","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2544","title":{"rendered":"Direct N-body Kernels for Multicore Platforms"},"content":{"rendered":"<p>We present an inter-architectural comparison of single-and double-precision direct n-body implementations on modern multicore platforms, including those based on the Intel Nehalem and AMD Barcelona systems, the Sony-Toshiba-IBM PowerXCell\/8i processor, and NVIDA Tesla C870 and C1060 GPU systems. We compare our implementations across platforms on a variety of proxy measures, including performance, coding complexity, and energy efficiency.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present an inter-architectural comparison of single-and double-precision direct n-body implementations on modern multicore platforms, including those based on the Intel Nehalem and AMD Barcelona systems, the Sony-Toshiba-IBM PowerXCell\/8i processor, and NVIDA Tesla C870 and C1060 GPU systems. We compare our implementations across platforms on a variety of proxy measures, including performance, coding complexity, and [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,3],"tags":[1782,14,258,20,199,202],"class_list":["post-2544","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-n-body-simulation","tag-nvidia","tag-tesla-c1060","tag-tesla-c870"],"views":1834,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2544","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=2544"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2544\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2544"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2544"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2544"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}