{"id":8600,"date":"2012-12-04T22:16:23","date_gmt":"2012-12-04T20:16:23","guid":{"rendered":"http:\/\/hgpu.org\/?p=8600"},"modified":"2012-12-04T22:16:23","modified_gmt":"2012-12-04T20:16:23","slug":"fusionsim-characterizing-the-performance-benefits-of-fused-cpugpu-systems","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8600","title":{"rendered":"FusionSim: Characterizing the Performance Benefits of Fused CPU\/GPU Systems"},"content":{"rendered":"<p>We present FusionSim, a modeling framework capable of cycle-accurate simulation of a complete x86-based computer system with (a) a CPU and a GPU on the same die, and (b) a CPU and a GPU connected as separate components. We use FusionSim to characterize the performance of the Rodinia benchmarks on fused and discrete systems. We demonstrate that the speed-up due to fusion is highly correlated with the input data size. We demonstrate that for benchmarks that benefit most from fusion, a 9.72x speed-up is possible for small problem sizes. This speedup reduces to 1.84x with medium problem sizes. We study a software-managed coherence solution for the fused system. We find that it imposes a minor performance overhead of 2% for most benchmarks. Finally, we develop an analytical model for the performance benefit that is to be expected from fusion and show that FusionSim follows the predicted performance trend.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present FusionSim, a modeling framework capable of cycle-accurate simulation of a complete x86-based computer system with (a) a CPU and a GPU on the same die, and (b) a CPU and a GPU connected as separate components. We use FusionSim to characterize the performance of the Rodinia benchmarks on fused and discrete systems. We [&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":[1355,153,451,1782,176,67,390],"class_list":["post-8600","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-amd-fusion","tag-analytical-model","tag-benchmarking","tag-computer-science","tag-package","tag-performance","tag-thesis"],"views":2482,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8600","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=8600"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8600\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8600"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8600"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8600"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}