{"id":2928,"date":"2011-02-21T14:49:13","date_gmt":"2011-02-21T14:49:13","guid":{"rendered":"http:\/\/hgpu.org\/?p=2928"},"modified":"2011-02-21T14:49:13","modified_gmt":"2011-02-21T14:49:13","slug":"software-based-ecc-for-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2928","title":{"rendered":"Software-Based ECC for GPUs"},"content":{"rendered":"<p>Commodity off-the-shelf GPUs lack error checking mechanisms for graphics memory, whereas conventional HPC platforms have used hardware-based ECC for DRAMs. To alleviate this reliability concern, we propose a software-based ECC for GPGPU applications. We add small program codes to normal CUDA programs that compute ECCs for data residing in graphics memory so that transient bit-flips can be detected or masked. Preliminary performance studies with 3-D FFT and the N-body problem show that error checking using ECC can take 200% and 7% of overhead, respectively. We discuss that performance overheads are derived from the cost of ECC computation on GPUs.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Commodity off-the-shelf GPUs lack error checking mechanisms for graphics memory, whereas conventional HPC platforms have used hardware-based ECC for DRAMs. To alleviate this reliability concern, we propose a software-based ECC for GPGPU applications. We add small program codes to normal CUDA programs that compute ECCs for data residing in graphics memory so that transient bit-flips [&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":[1782,14,272,207,258,20,357,251,244],"class_list":["post-2928","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-error-recovery","tag-fft","tag-n-body-simulation","tag-nvidia","tag-nvidia-geforce-8800-gts","tag-nvidia-geforce-gtx-285","tag-tesla-s1070"],"views":2198,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2928","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=2928"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2928\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2928"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2928"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2928"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}