{"id":6214,"date":"2011-11-08T18:41:44","date_gmt":"2011-11-08T16:41:44","guid":{"rendered":"http:\/\/hgpu.org\/?p=6214"},"modified":"2011-11-08T18:41:44","modified_gmt":"2011-11-08T16:41:44","slug":"gpu-cluster-with-matlab","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6214","title":{"rendered":"GPU Cluster with MATLAB"},"content":{"rendered":"<p>This paper presents the architecture of an heterogeneous cluster where each node has one or more Graphical Unit Processors (GPUs). The motivation of the work is the fact that this technology presents very impressive results in High Performance Computing at a very low cost and very small energy consumption so. Although this might not be a huge novelty, it is the fact that it can be programmed using MATLAB (one of the scientist&#8217;s favourite programs). As an example of application, an implementation of the k-Nearest Neighbours will be executed on the platform using both parallelism techniques: MPI and CUDA).<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents the architecture of an heterogeneous cluster where each node has one or more Graphical Unit Processors (GPUs). The motivation of the work is the fact that this technology presents very impressive results in High Performance Computing at a very low cost and very small energy consumption so. Although this might not be [&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":[11,89,3],"tags":[1782,14,106,452,242,349,20,674,411,1232],"class_list":["post-6214","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-gpu-cluster","tag-heterogeneous-systems","tag-mpi","tag-nearest-neighbour","tag-nvidia","tag-nvidia-geforce-8400-gs","tag-nvidia-geforce-9800-gtx","tag-nvidia-geforce-gts-450"],"views":2384,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6214","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=6214"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6214\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6214"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6214"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6214"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}