{"id":7414,"date":"2012-04-10T16:53:59","date_gmt":"2012-04-10T13:53:59","guid":{"rendered":"http:\/\/hgpu.org\/?p=7414"},"modified":"2012-04-10T16:53:59","modified_gmt":"2012-04-10T13:53:59","slug":"a-comparative-study-of-parallel-algorithms-for-the-girth-problem","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7414","title":{"rendered":"A Comparative Study of Parallel Algorithms for the Girth Problem"},"content":{"rendered":"<p>In this paper we introduce efficient parallel algorithms for finding the girth in a graph or digraph, where girth is the length of a shortest cycle. We empirically compare our algorithms by using two common APIs for parallel programming in C++, which are OpenMP for multiple CPUs and CUDA for multi-core GPUs. We conclude that both hardware platforms and programming models have their benefits.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we introduce efficient parallel algorithms for finding the girth in a graph or digraph, where girth is the length of a shortest cycle. We empirically compare our algorithms by using two common APIs for parallel programming in C++, which are OpenMP for multiple CPUs and CUDA for multi-core GPUs. We conclude that [&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":[36,11,89,3],"tags":[1787,1782,14,20,378],"class_list":["post-7414","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-nvidia","tag-tesla-c2050"],"views":2569,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7414","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=7414"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7414\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7414"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7414"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7414"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}