{"id":5640,"date":"2011-09-21T14:19:42","date_gmt":"2011-09-21T11:19:42","guid":{"rendered":"http:\/\/hgpu.org\/?p=5640"},"modified":"2011-09-21T14:19:42","modified_gmt":"2011-09-21T11:19:42","slug":"parallel-graduated-assignment-algorithm-for-multiple-graph-matching-based-on-a-common-labelling","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5640","title":{"rendered":"Parallel graduated assignment algorithm for multiple graph matching based on a common labelling"},"content":{"rendered":"<p>This paper presents a new parallel algorithm to compute multiple graph-matching based on the Graduated Assignment. The aim of developing this parallel algorithm is to perform multiple graph matching in a current desktop computer, but, instead of executing the code in the generic processor, we execute a parallel code in the graphic processor unit. Our new algorithm is ready to take advantage of incoming desktop computers capabilities. While comparing the classical algorithm (executed in the main processor) respect our parallel algorithm (executed in the graphic processor unit), experiments show an important speed-up of the run time.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents a new parallel algorithm to compute multiple graph-matching based on the Graduated Assignment. The aim of developing this parallel algorithm is to perform multiple graph matching in a current desktop computer, but, instead of executing the code in the generic processor, we execute a parallel code in the graphic processor unit. Our [&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":[1787,1782,14,158,20,531,119],"class_list":["post-5640","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-ion","tag-presentation"],"views":2110,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5640","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=5640"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5640\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5640"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5640"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5640"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}