In this paper we assess the neutron sensitivity of Graphics Processing Units (GPUs) when executing a Fast Fourier Transform (FFT) algorithm, and propose specific software-based hardening strategies to reduce its failure rate. Our research is motivated by experimental results with an unhardened FFT that demonstrate a majority of multiple errors in the output in the case of failures, which are caused by data dependencies. In addition, the use of the built-in error-correction code (ECC) showed a large overhead, and proved to be insufficient to provide high reliability. Experimental results with the hardened algorithm show a two orders of magnitude failure rate improvement over the original algorithm (one order of magnitude over ECC) and an overhead 64% smaller than ECC.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this paper we assess the neutron sensitivity of Graphics Processing Units (GPUs) when executing a Fast Fourier Transform (FFT) algorithm, and propose specific software-based hardening strategies to reduce its failure rate. Our research is motivated by experimental results with an unhardened FFT that demonstrate a majority of multiple errors in the output in the […]<\/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":[11,89,3],"tags":[1782,14,1189,207,20,378],"class_list":["post-12215","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-fft","tag-nvidia","tag-tesla-c2050"],"views":2246,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12215","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=12215"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12215\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=12215"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=12215"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=12215"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}