{"id":2896,"date":"2011-02-18T17:47:47","date_gmt":"2011-02-18T17:47:47","guid":{"rendered":"http:\/\/hgpu.org\/?p=2896"},"modified":"2011-02-18T17:47:47","modified_gmt":"2011-02-18T17:47:47","slug":"optimization-of-hep-codes-on-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2896","title":{"rendered":"Optimization of HEP codes on GPUs"},"content":{"rendered":"<p>The graphics processor units (GPUs) have evolved into high-performance co-processors that can be easily programmed with common high-level language such as C, Fortran and C++. Today&#8217;s GPUs greatly outpace CPUs in arithmetic performance and memory bandwidth, making them the ideal coprocessor to accelerate a variety of data parallel applications. Here, we shall describe the application of the data parallelism model supported in CUDA and GPUs with some example usage in high-energy physics software.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The graphics processor units (GPUs) have evolved into high-performance co-processors that can be easily programmed with common high-level language such as C, Fortran and C++. Today&#8217;s GPUs greatly outpace CPUs in arithmetic performance and memory bandwidth, making them the ideal coprocessor to accelerate a variety of data parallel applications. Here, we shall describe the application [&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":[89,3,12],"tags":[14,99,20,992,226,379,967,298,1783,199],"class_list":["post-2896","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-paper","category-physics","tag-cuda","tag-high-energy-physics-experiment","tag-nvidia","tag-nvidia-geforce-8400-gt","tag-nvidia-geforce-8800-gt","tag-nvidia-geforce-gtx-480","tag-nvidia-quadro-nvs-290","tag-optimization","tag-physics","tag-tesla-c1060"],"views":3132,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2896","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=2896"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2896\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2896"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2896"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2896"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}