{"id":993,"date":"2010-10-28T15:23:30","date_gmt":"2010-10-28T15:23:30","guid":{"rendered":"http:\/\/hgpu.org\/?p=993"},"modified":"2010-10-28T15:23:30","modified_gmt":"2010-10-28T15:23:30","slug":"motion-compensation-and-reconstruction-of-h-264avc-video-bitstreams-using-the-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=993","title":{"rendered":"Motion Compensation and Reconstruction of H.264\/AVC Video Bitstreams using the GPU"},"content":{"rendered":"<p>Most modern computers are equipped with powerful yet cost-effective graphics processing units (GPUs) to accelerate graphics operations. Although programmable shaders on these GPUs were designed for the creation of 3-D rendering effects, they can also be used as generic processing units for vector data. This paper proposes a hardware Tenderer capable of executing motion compensation, reconstruction, and visualization entirely on the GPU by the use of vertex and pixel shaders. Our measurements show that a speedup of 297% can be achieved by relying on the processing power of the GPU, relative to the CPU. As an example, real-time playback of high-definition video (1080 p) was achieved at 62.0 frames per second, consuming only 68.2% of all CPU cycles on a modern machine.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Most modern computers are equipped with powerful yet cost-effective graphics processing units (GPUs) to accelerate graphics operations. Although programmable shaders on these GPUs were designed for the creation of 3-D rendering effects, they can also be used as generic processing units for vector data. This paper proposes a hardware Tenderer capable of executing motion compensation, [&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":[1782,14,125,126,20,301,247],"class_list":["post-993","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-h-264avc","tag-motion-compensation","tag-nvidia","tag-nvidia-geforce-6800-gt","tag-nvidia-geforce-7800-gtx"],"views":2692,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/993","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=993"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/993\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=993"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=993"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=993"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}