{"id":6502,"date":"2011-12-06T18:05:10","date_gmt":"2011-12-06T16:05:10","guid":{"rendered":"http:\/\/hgpu.org\/?p=6502"},"modified":"2011-12-06T18:05:10","modified_gmt":"2011-12-06T16:05:10","slug":"multiprocessing-acceleration-of-h-264avc-motion-estimation-full-search-algorithm-under-cuda-architecture","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6502","title":{"rendered":"Multiprocessing Acceleration of H.264\/AVC Motion Estimation Full Search Algorithm under CUDA Architecture"},"content":{"rendered":"<p>This work presents a parallel GPU-based solution for the Motion Estimation (ME) process in a videoencoding system. We propose a way to partition the steps of Full Search block matching algorithm in the CUDA architecture, and to compare the performance with a theoretical model and two implementations (sequential and parallel using OpenMP library). We obtained a O(n2\/log2n) speed-up which fits the theoretical model considering different search areas. It represents up to 600x gain compared to the serial implementation, and 66x compared to the parallel OpenMP implementation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This work presents a parallel GPU-based solution for the Motion Estimation (ME) process in a videoencoding system. We propose a way to partition the steps of Full Search block matching algorithm in the CUDA architecture, and to compare the performance with a theoretical model and two implementations (sequential and parallel using OpenMP library). We obtained [&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":[36,89,33,3],"tags":[1787,14,125,1786,20,379],"class_list":["post-6502","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-image-processing","category-paper","tag-algorithms","tag-cuda","tag-h-264avc","tag-image-processing","tag-nvidia","tag-nvidia-geforce-gtx-480"],"views":2395,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6502","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=6502"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6502\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6502"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6502"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6502"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}