Architecture designers tend to integrate both CPU and GPU on the same chip to deliver energy-efficient designs. To effectively leverage the power of both CPUs and GPUs on integrated architectures, researchers have recently put substantial efforts into co-running a single application on both the CPU and the GPU of such architectures. However, few studies have been performed to analyze a wide range of parallel computation patterns on such architectures. In this paper, we port all programs in Rodinia benchmark suite and co-run these programs on the integrated architecture. We find that co-running results are not always better than running the application on the CPU only or the GPU only. Among the 20 programs, 3 programs can benefit from co-running, 12 programs using GPU only and 2 programs using CPU only achieve the best performance. The remaining 3 programs show no performance preference for different devices. We also characterize the workload and summarize the patterns for the system insights of co-running on integrated architectures.<\/p>\n","protected":false},"excerpt":{"rendered":"
Architecture designers tend to integrate both CPU and GPU on the same chip to deliver energy-efficient designs. To effectively leverage the power of both CPUs and GPUs on integrated architectures, researchers have recently put substantial efforts into co-running a single application on both the CPU and the GPU of such architectures. However, few studies have […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,90,3],"tags":[451,1782,1793,176],"class_list":["post-15764","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-benchmarking","tag-computer-science","tag-opencl","tag-package"],"views":1985,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/15764","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=15764"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/15764\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=15764"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=15764"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=15764"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}