{"id":7622,"date":"2012-05-20T22:42:33","date_gmt":"2012-05-20T19:42:33","guid":{"rendered":"http:\/\/hgpu.org\/?p=7606"},"modified":"2012-06-15T12:35:12","modified_gmt":"2012-06-15T09:35:12","slug":"computing-2d-alpha-shapes-using-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7622","title":{"rendered":"Computing 2D Alpha Shapes Using GPU"},"content":{"rendered":"<p>This report presents an approach to compute Alpha Shapes for a 2D un-weighted point set using the graphics processing unit (GPU). The problem of alpha shapes has been well-defined and algorithms have been developed to compute it efficiently in 2D and 3D using CPU. However, the nature of this problem makes it well-suited for solving it in parallel and hence, can gain potential speedup over sequential implementations. The fine-grained parallelism offered by the GPU can be harnessed for this purpose. Our implementation using the CUDA programming model on NVidia GPUs is numerically robust and runs faster than existing CPU algorithms.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This report presents an approach to compute Alpha Shapes for a 2D un-weighted point set using the graphics processing unit (GPU). The problem of alpha shapes has been well-defined and algorithms have been developed to compute it efficiently in 2D and 3D using CPU. However, the nature of this problem makes it well-suited for solving [&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":[36,11,89,3],"tags":[1787,1782,14,20,974,176],"class_list":["post-7622","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-nvidia-cuda","category-paper","tag-algorithms","tag-computer-science","tag-cuda","tag-nvidia","tag-nvidia-geforce-gtx-580","tag-package"],"views":2145,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7622","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=7622"}],"version-history":[{"count":1,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7622\/revisions"}],"predecessor-version":[{"id":7758,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7622\/revisions\/7758"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7622"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7622"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7622"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}