{"id":2954,"date":"2011-02-24T22:12:12","date_gmt":"2011-02-24T22:12:12","guid":{"rendered":"http:\/\/hgpu.org\/?p=2954"},"modified":"2011-02-24T22:12:12","modified_gmt":"2011-02-24T22:12:12","slug":"many-core-gpu-computing-with-nvidia-cuda","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2954","title":{"rendered":"Many-core GPU computing with NVIDIA CUDA"},"content":{"rendered":"<p>In the past, graphics processors were special-purpose hardwired application accelerators, suitable only for conventional graphics applications. Modern GPUs are fully programmable, massively parallel floating point processors. In this talk I will describe NVIDIA&#8217;s scalable, highly parallel many-core GPU architecture and how CUDA software for GPU computing delivers high throughput for data-intensive processing. I will discuss how CUDA is reinvigorating research on data-parallel algorithms, reducing time to scientific discovery, and enabling a variety of compute-intensive industrial applications of GPUs beyond computer graphics.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In the past, graphics processors were special-purpose hardwired application accelerators, suitable only for conventional graphics applications. Modern GPUs are fully programmable, massively parallel floating point processors. In this talk I will describe NVIDIA&#8217;s scalable, highly parallel many-core GPU architecture and how CUDA software for GPU computing delivers high throughput for data-intensive processing. I will discuss [&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":[11,89,3],"tags":[1782,14,95,20,660],"class_list":["post-2954","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-high-level-languages","tag-nvidia","tag-programming-languages"],"views":1874,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2954","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=2954"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2954\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2954"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2954"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2954"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}