{"id":8937,"date":"2013-02-14T21:44:47","date_gmt":"2013-02-14T19:44:47","guid":{"rendered":"http:\/\/hgpu.org\/?p=8937"},"modified":"2013-02-14T21:44:47","modified_gmt":"2013-02-14T19:44:47","slug":"enhancing-performance-of-meshfree-methods-by-hybrid-computing","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8937","title":{"rendered":"Enhancing Performance of Meshfree Methods by Hybrid Computing"},"content":{"rendered":"<p>Hybrid computing technique is used in this study to significantly enhance the performance of meshfree methods. These methods are typically slower than finite element methods (FEM) mostly because their stiffness matrices are much denser ones formed by FEM. As a result, both forming stiffness matrices and solving equations are much slower. In this paper, we report our use of NVidia based accelerators and CUDA programing techniques. We also demonstrate that our hybrid computing technique is generally applicable to most meshfree methods, and can significantly boost their performance. Further performance improvements are possible by porting more portions of our code from host to device.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Hybrid computing technique is used in this study to significantly enhance the performance of meshfree methods. These methods are typically slower than finite element methods (FEM) mostly because their stiffness matrices are much denser ones formed by FEM. As a result, both forming stiffness matrices and solving equations are much slower. In this paper, we [&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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,3],"tags":[1782,14,1037,212,555,20,378],"class_list":["post-8937","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-fem","tag-finite-element-method","tag-hybrid-computing","tag-nvidia","tag-tesla-c2050"],"views":2296,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8937","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=8937"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8937\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8937"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8937"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8937"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}