{"id":5958,"date":"2011-10-20T14:25:44","date_gmt":"2011-10-20T11:25:44","guid":{"rendered":"http:\/\/hgpu.org\/?p=5958"},"modified":"2011-10-20T14:25:44","modified_gmt":"2011-10-20T11:25:44","slug":"peppher-efficient-and-productive-usage-of-hybrid-computing-systems","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5958","title":{"rendered":"PEPPHER: Efficient and Productive Usage of Hybrid Computing Systems"},"content":{"rendered":"<p>PEPPHER, a three-year European FP7 project, addresses efficient utilization of hybrid (heterogeneous) computer systems consisting of multicore CPUs with GPU-type accelerators. This article outlines the PEPPHER performance-aware component model, performance prediction means, runtime system, and other aspects of the project. A larger example demonstrates performance portability with the PEPPHER approach across hybrid systems with one to four GPUs.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>PEPPHER, a three-year European FP7 project, addresses efficient utilization of hybrid (heterogeneous) computer systems consisting of multicore CPUs with GPU-type accelerators. This article outlines the PEPPHER performance-aware component model, performance prediction means, runtime system, and other aspects of the project. A larger example demonstrates performance portability with the PEPPHER approach across hybrid systems with one [&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":[11,90,3],"tags":[215,1782,452,555,20,1793,199],"class_list":["post-5958","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-code-generation","tag-computer-science","tag-heterogeneous-systems","tag-hybrid-computing","tag-nvidia","tag-opencl","tag-tesla-c1060"],"views":1672,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5958","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=5958"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5958\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5958"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5958"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5958"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}