{"id":9814,"date":"2013-07-07T00:18:43","date_gmt":"2013-07-06T21:18:43","guid":{"rendered":"http:\/\/hgpu.org\/?p=9814"},"modified":"2013-07-07T00:18:43","modified_gmt":"2013-07-06T21:18:43","slug":"comparison-of-rectangular-matrix-multiplication-with-and-without-border-conditions","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=9814","title":{"rendered":"Comparison of Rectangular Matrix Multiplication with and without Border Conditions"},"content":{"rendered":"<p>Matrix multiplication algorithms are very common and widely used for computation in almost any field. There are many implementations for matrix multiplication on different platforms and programming models. GPU devices in the recent years have become powerful computational units that have entered the segment of high performance computing. In this paper we are analysing two approaches for the matrix multiplication algorithm with and without border conditions for parallel GPU execution.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Matrix multiplication algorithms are very common and widely used for computation in almost any field. There are many implementations for matrix multiplication on different platforms and programming models. GPU devices in the recent years have become powerful computational units that have entered the segment of high performance computing. In this paper we are analysing two [&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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,11,89,3],"tags":[1787,1782,14,324,20,1306],"class_list":["post-9814","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-matrix-multiplication","tag-nvidia","tag-nvidia-geforce-gtx-680"],"views":2021,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/9814","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=9814"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/9814\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9814"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9814"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9814"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}