{"id":17111,"date":"2017-04-05T10:44:30","date_gmt":"2017-04-05T07:44:30","guid":{"rendered":"https:\/\/hgpu.org\/?p=17111"},"modified":"2017-04-05T10:44:30","modified_gmt":"2017-04-05T07:44:30","slug":"the-second-international-workshop-on-gpu-computing-and-applications-gca-2017","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=17111","title":{"rendered":"The Second International Workshop on GPU Computing and Applications (GCA), 2017"},"content":{"rendered":"<p>Built for massive parallelism, General Purpose computing on Graphic<br \/>\nProcessing Unit (GPGPU) has superseded high-performance CPU in several<br \/>\nimportant tasks, including computer graphics, physics calculations,<br \/>\nencryption\/decryption and scientific computations.<\/p>\n<p>The goal of this workshop is to provide a forum to discuss and evaluate<br \/>\nemerging techniques, platforms and applications capable of harvesting the<br \/>\npower of current GPGPUs.<\/p>\n<p>The GCA workshop seeks for high-quality papers on various topics, including but not limited to:<\/p>\n<ul>\n<li>GPU applications<\/li>\n<li>Computer graphics on GPUs<\/li>\n<li>GPU compilation<\/li>\n<li>GPU programming environments<\/li>\n<li>GPU power efficiency<\/li>\n<li>GPU architectures<\/li>\n<li>GPU theoretical computing models<\/li>\n<li>GPU benchmarking\/measurements<\/li>\n<li>GPU embedded systems<\/li>\n<li>Multi-GPU systems<\/li>\n<li>GPU cluster<\/li>\n<li>Heterogeneous GPU platforms<\/li>\n<li>CPU-GPU cooperation<\/li>\n<li>CUDA\/OpenCL\/OpenACC<\/li>\n<li>Deep learning on GPUs<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Built for massive parallelism, General Purpose computing on Graphic Processing Unit (GPGPU) has superseded high-performance CPU in several important tasks, including computer graphics, physics calculations, encryption\/decryption and scientific computations. The goal of this workshop is to provide a forum to discuss and evaluate emerging techniques, platforms and applications capable of harvesting the power of current [&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":[86],"tags":[],"class_list":["post-17111","post","type-post","status-publish","format-standard","hentry","category-events"],"views":1959,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/17111","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=17111"}],"version-history":[{"count":3,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/17111\/revisions"}],"predecessor-version":[{"id":17116,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/17111\/revisions\/17116"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=17111"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=17111"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=17111"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}