{"id":8461,"date":"2012-11-06T22:52:38","date_gmt":"2012-11-06T20:52:38","guid":{"rendered":"http:\/\/hgpu.org\/?p=8461"},"modified":"2012-11-06T22:52:38","modified_gmt":"2012-11-06T20:52:38","slug":"all-pairs-shortest-path-algorithms-using-cuda","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8461","title":{"rendered":"All-Pairs Shortest Path Algorithms Using CUDA"},"content":{"rendered":"<p>Utilising graph theory is a common activity in computer science. Algorithms that perform computations on large graphs are not always cost effective, requiring supercomputers to achieve results in a practical amount of time. Graphics Processing Units provide a cost effective alternative to supercomputers, allowing parallel algorithms to be executed directly on the Graphics Processing Unit. Several algorithms exist to solve the All-Pairs Shortest Path problem on the Graphics Processing Unit, but it can be difficult to determine whether the claims made are true and verify the results listed. This research asks &quot;Which All-Pairs Shortest Path algorithms solve the All-Pairs Shortest Path problem the fastest, and can the authors&#8217; claims be verified?&quot; The results we obtain when answering this question show why it is important to be able to collate existing work, and analyse them on a common platform to observe fair results retrieved from a single system. In this way, the research shows us how effective each algorithm is at performing its task, and suggest when a certain algorithm might be used over another.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Utilising graph theory is a common activity in computer science. Algorithms that perform computations on large graphs are not always cost effective, requiring supercomputers to achieve results in a practical amount of time. Graphics Processing Units provide a cost effective alternative to supercomputers, allowing parallel algorithms to be executed directly on the Graphics Processing Unit. [&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":[1787,1782,14,158,20,953,442,390],"class_list":["post-8461","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-graph-theory","tag-nvidia","tag-nvidia-geforce-gtx-470","tag-path-problems","tag-thesis"],"views":2899,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8461","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=8461"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8461\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8461"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8461"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8461"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}