{"id":10513,"date":"2013-09-11T23:40:03","date_gmt":"2013-09-11T20:40:03","guid":{"rendered":"http:\/\/hgpu.org\/?p=10513"},"modified":"2013-09-11T23:40:03","modified_gmt":"2013-09-11T20:40:03","slug":"histogram-computations-on-gpus-kernel-using-global-and-shared-memory-atomics","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=10513","title":{"rendered":"Histogram Computations on GPUs Kernel using Global and Shared Memory Atomics"},"content":{"rendered":"<p>In this paper we implement histogram computations on a Graphics Processing Unit (GPU). Our Histogram computations is implemented using compute unified device architecture (CUDA) which is a minimal extension to C\/C++. In this development Histogram computations, computed on GPU&#8217;s global memory as well as on shared memory. We also perform Histogram computations on CPU and consider it as a baseline performance. Experimental results demonstrate that shared memory in GPU gives seven times speedup over our baseline CPU.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we implement histogram computations on a Graphics Processing Unit (GPU). Our Histogram computations is implemented using compute unified device architecture (CUDA) which is a minimal extension to C\/C++. In this development Histogram computations, computed on GPU&#8217;s global memory as well as on shared memory. We also perform Histogram computations on CPU and [&hellip;]<\/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":[11,89,3],"tags":[1782,14,884,20,1494],"class_list":["post-10513","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-memory","tag-nvidia","tag-nvidia-geforce-gt-610"],"views":4125,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10513","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=10513"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10513\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10513"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10513"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10513"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}