{"id":1225,"date":"2010-11-05T21:44:24","date_gmt":"2010-11-05T21:44:24","guid":{"rendered":"http:\/\/hgpu.org\/?p=1225"},"modified":"2010-11-05T21:44:24","modified_gmt":"2010-11-05T21:44:24","slug":"gpus-for-event-reconstruction-in-the-fairroot-framework","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=1225","title":{"rendered":"GPU&#8217;s for event reconstruction in the FairRoot framework"},"content":{"rendered":"<p>FairRoot is the simulation and analysis framework used by CBM and PANDA experiments at FAIR\/GSI. The use of graphics processor units (GPUs) for event reconstruction in FairRoot will be presented. The fact that CUDA (Nvidia&#8217;s Compute Unified Device Architecture) development tools work alongside the conventional C\/C++ compiler, makes it possible to mix GPU code with general-purpose code for the host CPU, based on this some of the reconstruction tasks can be send to the graphic cards. Moreover, tasks that run on the GPU&#8217;s can also run in emulation mode on the host CPU, which has the advantage that the same code is used on both CPU and GPU.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>FairRoot is the simulation and analysis framework used by CBM and PANDA experiments at FAIR\/GSI. The use of graphics processor units (GPUs) for event reconstruction in FairRoot will be presented. The fact that CUDA (Nvidia&#8217;s Compute Unified Device Architecture) development tools work alongside the conventional C\/C++ compiler, makes it possible to mix GPU code with [&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":[14,471,472,20,176,470,1783,199],"class_list":["post-1225","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-paper","category-physics","tag-cuda","tag-instrumentation-and-measurement","tag-nuclear-physics","tag-nvidia","tag-package","tag-particle-physics-and-field-theory","tag-physics","tag-tesla-c1060"],"views":2970,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1225","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=1225"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1225\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1225"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1225"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1225"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}