{"id":10104,"date":"2013-07-21T23:45:15","date_gmt":"2013-07-21T20:45:15","guid":{"rendered":"http:\/\/hgpu.org\/?p=10104"},"modified":"2013-07-21T23:45:15","modified_gmt":"2013-07-21T20:45:15","slug":"experimental-evaluation-of-thread-distribution-effects-on-multiple-output-errors-in-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=10104","title":{"rendered":"Experimental Evaluation of Thread Distribution Effects on Multiple Output Errors in GPUs"},"content":{"rendered":"<p>Graphic Processing Units are very prone to be corrupted by neutrons. Experimental results show that in the majority of the cases a typical application like matrix multiplication is affected by multiple output errors. In this paper we evaluate how different thread distributions impact the multiple output errors occurrence. The reported results and the performed architecture analysis give practical programming advices that may increase the reliability of a generic parallel algorithm without introducing any hardware or computation overhead.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphic Processing Units are very prone to be corrupted by neutrons. Experimental results show that in the majority of the cases a typical application like matrix multiplication is affected by multiple output errors. In this paper we evaluate how different thread distributions impact the multiple output errors occurrence. The reported results and the performed architecture [&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":[11,89,3],"tags":[1782,14,1189,20,379],"class_list":["post-10104","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-fault-tolerance","tag-nvidia","tag-nvidia-geforce-gtx-480"],"views":2283,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10104","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=10104"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10104\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10104"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10104"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10104"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}