{"id":3975,"date":"2011-05-15T20:29:26","date_gmt":"2011-05-15T20:29:26","guid":{"rendered":"http:\/\/hgpu.org\/?p=3975"},"modified":"2011-05-15T20:29:26","modified_gmt":"2011-05-15T20:29:26","slug":"a-gpu-algorithm-for-ic-floorplanning-specification-analysis-and-optimization","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=3975","title":{"rendered":"A GPU Algorithm for IC Floorplanning: Specification, Analysis and Optimization"},"content":{"rendered":"<p>In this paper, we propose a novel floor planning algorithm for GPUs. Floor planning is an inherently sequential algorithm, far from the typical programs suitable for Single Instruction Multiple Thread (SIMT) style concurrency in a GPU. We propose a fundamentally different approach of exploring the floor plan solution space, where we evaluate concurrent moves on a given floor plan. We illustrate several performance optimization techniques for this algorithm in GPUs. Compared to the sequential algorithm, our techniques achieve 4-30X speedup for a range of MCNC benchmarks, while delivering comparable or better solution quality.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper, we propose a novel floor planning algorithm for GPUs. Floor planning is an inherently sequential algorithm, far from the typical programs suitable for Single Instruction Multiple Thread (SIMT) style concurrency in a GPU. We propose a fundamentally different approach of exploring the floor plan solution space, where we evaluate concurrent moves on [&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":[1787,596,1782],"class_list":["post-3975","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-paper","tag-algorithms","tag-cad","tag-computer-science"],"views":2139,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3975","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=3975"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3975\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3975"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3975"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3975"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}