{"id":16822,"date":"2016-12-17T12:11:03","date_gmt":"2016-12-17T10:11:03","guid":{"rendered":"http:\/\/hgpu.org\/?p=16822"},"modified":"2016-12-17T12:11:03","modified_gmt":"2016-12-17T10:11:03","slug":"parallel-level-set-algorithm-with-mpi-and-accelerated-on-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=16822","title":{"rendered":"Parallel Level set algorithm with MPI and accelerated on GPU"},"content":{"rendered":"<p>Level set method has been used to capture interface motion. Narrow band algorithm is applied to localize the solving of level-set PDE on global domain to a tube around interface. Due to the unknown evolving interface, narrow band algorithm brings load balance problem for parallelizing computing. This work presents a tool for evenly distributing work loads on CPUs. On the other hand, numerically solving level-set PDE only needs simple operations but on large grid points. This work also presents a GPU acceleration for solving level-set PDE using finite difference method.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Level set method has been used to capture interface motion. Narrow band algorithm is applied to localize the solving of level-set PDE on global domain to a tube around interface. Due to the unknown evolving interface, narrow band algorithm brings load balance problem for parallelizing computing. This work presents a tool for evenly distributing work [&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":[89,3,12],"tags":[98,14,327,242,20,176,551,1783],"class_list":["post-16822","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-paper","category-physics","tag-computational-physics","tag-cuda","tag-finite-difference","tag-mpi","tag-nvidia","tag-package","tag-pdes","tag-physics"],"views":2453,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/16822","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=16822"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/16822\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=16822"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=16822"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=16822"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}