{"id":11657,"date":"2014-03-17T00:34:35","date_gmt":"2014-03-16T22:34:35","guid":{"rendered":"http:\/\/hgpu.org\/?p=11657"},"modified":"2014-03-17T00:34:35","modified_gmt":"2014-03-16T22:34:35","slug":"an-optimized-algorithm-for-discrete-element-system-analysis-using-cuda","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11657","title":{"rendered":"An optimized algorithm for discrete element system analysis using CUDA"},"content":{"rendered":"<p>In this paper a parallel computing algorithm for discrete element systems is presented. The discrete model is consisted of finite elements and contacts among the elements. The algorithm is realized using C++ and CUDA and was optimized for NVIDIA GPUs. As a result, the performance of the GPU code is 43 times faster than the sequential code on CPU. The parallel algorithm, the optimism strategy, and the test results are discussed.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper a parallel computing algorithm for discrete element systems is presented. The discrete model is consisted of finite elements and contacts among the elements. The algorithm is realized using C++ and CUDA and was optimized for NVIDIA GPUs. As a result, the performance of the GPU code is 43 times faster than the [&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":[36,11,89,3],"tags":[1787,1782,14,212,20,251,1015,379,974,1006],"class_list":["post-11657","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-nvidia-cuda","category-paper","tag-algorithms","tag-computer-science","tag-cuda","tag-finite-element-method","tag-nvidia","tag-nvidia-geforce-gtx-285","tag-nvidia-geforce-gtx-460","tag-nvidia-geforce-gtx-480","tag-nvidia-geforce-gtx-580","tag-tesla-c2070"],"views":2267,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11657","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=11657"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11657\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11657"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11657"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11657"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}