{"id":6809,"date":"2012-01-03T00:01:58","date_gmt":"2012-01-02T22:01:58","guid":{"rendered":"http:\/\/hgpu.org\/?p=6809"},"modified":"2012-01-03T00:01:58","modified_gmt":"2012-01-02T22:01:58","slug":"an-optimal-k-exclusion-real-time-locking-protocol-motivated-by-multi-gpu-systems","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6809","title":{"rendered":"An optimal k-exclusion real-time locking protocol motivated by multi-GPU systems"},"content":{"rendered":"<p>Graphics processing units (GPUs) are becoming increasingly important in today&#8217;s platforms as their increased generality allows for them to be used as powerful co-processors. In previous work, we have found that GPUs may be integrated into real-time systems through the treatment of GPUs as shared resources, allocated to real-time tasks through mutual exclusion locking protocols. In this paper, we present an optimal k-exclusion locking protocol for globally-scheduled job-level static-priority (JLSP) systems. This protocol may be used to manage a pool of GPU resources in such systems.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphics processing units (GPUs) are becoming increasingly important in today&#8217;s platforms as their increased generality allows for them to be used as powerful co-processors. In previous work, we have found that GPUs may be integrated into real-time systems through the treatment of GPUs as shared resources, allocated to real-time tasks through mutual exclusion locking protocols. [&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":[36,11,3],"tags":[1787,1782,106,854],"class_list":["post-6809","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-paper","tag-algorithms","tag-computer-science","tag-gpu-cluster","tag-task-scheduling"],"views":2092,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6809","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=6809"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6809\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6809"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6809"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6809"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}