{"id":4372,"date":"2011-06-17T13:06:33","date_gmt":"2011-06-17T13:06:33","guid":{"rendered":"http:\/\/hgpu.org\/?p=4372"},"modified":"2011-06-17T13:06:33","modified_gmt":"2011-06-17T13:06:33","slug":"coarse-grain-computation-communication-overlap-for-efficient-application-level-checkpointing-for-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4372","title":{"rendered":"Coarse grain computation-communication overlap for efficient application-level checkpointing for GPUs"},"content":{"rendered":"<p>Graphics Processing Units (GPUs) are increasingly used to solve non-graphical scientific problems. However, it has been shown that the reliability of the GPUs is a concern because of the occurrence of the soft and hard errors. The checkpoint\/restart is the most commonly used technique to achieve fault tolerance in the presence of failures. This work present an application-level checkpoint scheme for systems composed of GPUs. Our scheme exploits the benefits of the divide-and-conquer technique and of the communication-computation overlapping to improve the execution time and checkpoint overhead. By dividing the problem and checkpointing in n subprocesses, we show that our scheme improves the checkpoint overhead by a factor of n. We also show that dividing the problem with finer granularity is not beneficial.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphics Processing Units (GPUs) are increasingly used to solve non-graphical scientific problems. However, it has been shown that the reliability of the GPUs is a concern because of the occurrence of the soft and hard errors. The checkpoint\/restart is the most commonly used technique to achieve fault tolerance in the presence of failures. This work [&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":[11,3],"tags":[1782,708],"class_list":["post-4372","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-fault-simulation"],"views":2144,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4372","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=4372"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4372\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4372"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4372"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4372"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}