{"id":3743,"date":"2011-04-29T11:13:31","date_gmt":"2011-04-29T11:13:31","guid":{"rendered":"http:\/\/hgpu.org\/?p=3743"},"modified":"2011-04-29T11:13:31","modified_gmt":"2011-04-29T11:13:31","slug":"finite-temperature-lattice-qcd-with-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=3743","title":{"rendered":"Finite temperature lattice QCD with GPUs"},"content":{"rendered":"<p>Graphics Processing Units (GPUs) are being used in many areas of physics, since the performance versus cost is very attractive. The GPUs can be addressed by CUDA which is a NVIDIA&#8217;s parallel computing architecture. It enables dramatic increases in computing performance by harnessing the power of the GPU. We present a performance comparison between the GPU and CPU with single precision and double precision in generating lattice SU(2) configurations. Analyses with single and multiple GPUs, using CUDA and OPENMP, are also presented. We also present SU(2) results for the renormalized Polyakov loop, colour averaged free energy and the string tension as a function of the temperature.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphics Processing Units (GPUs) are being used in many areas of physics, since the performance versus cost is very attractive. The GPUs can be addressed by CUDA which is a NVIDIA&#8217;s parallel computing architecture. It enables dramatic increases in computing performance by harnessing the power of the GPU. We present a performance comparison between the [&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":[14,110,72,20,436,379,252,1783,335],"class_list":["post-3743","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-paper","category-physics","tag-cuda","tag-high-energy-physics-lattice","tag-monte-carlo-simulation","tag-nvidia","tag-nvidia-geforce-gtx-295","tag-nvidia-geforce-gtx-480","tag-openmp","tag-physics","tag-qcd"],"views":1980,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3743","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=3743"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3743\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3743"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3743"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3743"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}