{"id":1368,"date":"2010-11-09T15:17:26","date_gmt":"2010-11-09T15:17:26","guid":{"rendered":"http:\/\/hgpu.org\/?p=1368"},"modified":"2010-11-09T15:17:26","modified_gmt":"2010-11-09T15:17:26","slug":"the-chamomile-scheme-an-optimized-algorithm-for-n-body-simulations-on-programmable-graphics-processing-units","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=1368","title":{"rendered":"The Chamomile Scheme: An Optimized Algorithm for N-body simulations on Programmable Graphics Processing Units"},"content":{"rendered":"<p>We present an algorithm named &#8220;Chamomile Scheme&#8221;. The scheme is fully optimized for calculating gravitational interactions on the latest programmable Graphics Processing Unit (GPU), NVIDIA GeForce8800GTX, which has (a) small but fast shared memories (16 K Bytes * 16) with no broadcasting mechanism and (b) floating point arithmetic hardware of 500 Gflop\/s but only for single precision. Based on this scheme, we have developed a library for gravitational N-body simulations, &#8220;CUNBODY-1&#8221;, whose measured performance reaches to 173 Gflop\/s for 2048 particles and 256 Gflop\/s for 131072 particles.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present an algorithm named &#8220;Chamomile Scheme&#8221;. The scheme is fully optimized for calculating gravitational interactions on the latest programmable Graphics Processing Unit (GPU), NVIDIA GeForce8800GTX, which has (a) small but fast shared memories (16 K Bytes * 16) with no broadcasting mechanism and (b) floating point arithmetic hardware of 500 Gflop\/s but only for [&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":[96,89,3],"tags":[1794,14,258,20,183,257],"class_list":["post-1368","post","type-post","status-publish","format-standard","hentry","category-astrophysics","category-nvidia-cuda","category-paper","tag-astrophysics","tag-cuda","tag-n-body-simulation","tag-nvidia","tag-nvidia-geforce-8800-gtx","tag-stellar-dynamics"],"views":2463,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1368","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=1368"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1368\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1368"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1368"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}