{"id":8303,"date":"2012-10-02T16:51:01","date_gmt":"2012-10-02T13:51:01","guid":{"rendered":"http:\/\/hgpu.org\/?p=8303"},"modified":"2012-10-02T16:51:01","modified_gmt":"2012-10-02T13:51:01","slug":"multi2sim-a-simulation-framework-for-cpu-gpu-computing","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8303","title":{"rendered":"Multi2Sim: a simulation framework for CPU-GPU computing"},"content":{"rendered":"<p>Accurate simulation is essential for the proper design and evaluation of any computing platform. Upon the current move toward the CPU-GPU heterogeneous computing era, researchers need a simulation framework that can model both kinds of computing devices and their interaction. In this paper, we present Multi2Sim, an open-source, modular, and fully configurable toolset that enables ISA-level simulation of an x86 CPU and an AMD Evergreen GPU. Focusing on a model of the AMD Radeon 5870 GPU, we address program emulation correctness, as well as architectural simulation accuracy, using AMD&#8217;s OpenCL benchmark suite. Simulation capabilities are demonstrated with a preliminary architectural exploration study, and workload characterization examples. The project source code, benchmark packages, and a detailed user&#8217;s guide are publicly available at www.multi2sim.org.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Accurate simulation is essential for the proper design and evaluation of any computing platform. Upon the current move toward the CPU-GPU heterogeneous computing era, researchers need a simulation framework that can model both kinds of computing devices and their interaction. In this paper, we present Multi2Sim, an open-source, modular, and fully configurable toolset that enables [&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":[7,455,451,1782,452,1793],"class_list":["post-8303","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-ati","tag-ati-radeon-hd-5870","tag-benchmarking","tag-computer-science","tag-heterogeneous-systems","tag-opencl"],"views":3471,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8303","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=8303"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8303\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8303"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8303"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8303"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}