{"id":13788,"date":"2015-03-28T23:09:48","date_gmt":"2015-03-28T21:09:48","guid":{"rendered":"http:\/\/hgpu.org\/?p=13788"},"modified":"2015-03-28T23:09:48","modified_gmt":"2015-03-28T21:09:48","slug":"shortest-path-queries-in-planar-graphs-on-gpu-accelerated-architectures","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=13788","title":{"rendered":"Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures"},"content":{"rendered":"<p>We develop an efficient parallel algorithm for answering shortest-path queries in planar graphs and implement it on a multi-node CPU\/GPU clusters. The algorithm uses a divide-and-conquer approach for decomposing the input graph into small and roughly equal subgraphs and constructs a distributed data structure containing shortest distances within each of those subgraphs and between their boundary vertices. For a planar graph with $n$ vertices, that data structure needs $O(n)$ storage per processor and allows queries to be answered in $O(n^{1\/4})$ time.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We develop an efficient parallel algorithm for answering shortest-path queries in planar graphs and implement it on a multi-node CPU\/GPU clusters. The algorithm uses a divide-and-conquer approach for decomposing the input graph into small and roughly equal subgraphs and constructs a distributed data structure containing shortest distances within each of those subgraphs and between their [&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":[11,3],"tags":[1782,94,510,350,106,20,442,1241],"class_list":["post-13788","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-data-structures-and-algorithms","tag-distributed-computing","tag-distributed-data-structures","tag-gpu-cluster","tag-nvidia","tag-path-problems","tag-tesla-m2090"],"views":2346,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/13788","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=13788"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/13788\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=13788"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=13788"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=13788"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}