{"id":12984,"date":"2014-10-25T21:29:44","date_gmt":"2014-10-25T18:29:44","guid":{"rendered":"http:\/\/hgpu.org\/?p=12984"},"modified":"2014-10-25T21:29:44","modified_gmt":"2014-10-25T18:29:44","slug":"gpgpu-acceleration-for-skeletal-animation-comparing-opencl-with-cuda-and-glsl","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=12984","title":{"rendered":"GPGPU Acceleration for Skeletal Animation-comparing OpenCL with CUDA and GLSL"},"content":{"rendered":"<p>The existing matrix palette algorithms for skeletal animation are accelerated by the technique GPGPU based on GLSL or CUDA. Because GLSL is extended from graphics library OpenGL, it couples the rendering and calculations together closely and forces itself not convenient to reuse, meanwhile CUDA is designed only for NVIDIA GPUs. In this paper GPGPU based on OpenCL is proposed for accelerating skeletal animations. OpenCL brings portability both on software and hardware. The experimental results show that the parallel scheme based on OpenCL can run on GPUs from AMD and NVIDIA. And the speedup is comparable with CUDA or GLSL.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The existing matrix palette algorithms for skeletal animation are accelerated by the technique GPGPU based on GLSL or CUDA. Because GLSL is extended from graphics library OpenGL, it couples the rendering and calculations together closely and forces itself not convenient to reuse, meanwhile CUDA is designed only for NVIDIA GPUs. In this paper GPGPU based [&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":[11,89,90,3],"tags":[7,1468,1782,14,187,20,627,1394,1793,182,67,144],"class_list":["post-12984","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-opencl","category-paper","tag-ati","tag-ati-radeon-hd-7750","tag-computer-science","tag-cuda","tag-glsl","tag-nvidia","tag-nvidia-geforce-gts-250","tag-nvidia-geforce-gtx-670","tag-opencl","tag-opengl","tag-performance","tag-rendering"],"views":4249,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12984","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=12984"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12984\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=12984"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=12984"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=12984"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}