{"id":3121,"date":"2011-03-06T21:41:01","date_gmt":"2011-03-06T21:41:01","guid":{"rendered":"http:\/\/hgpu.org\/?p=3121"},"modified":"2011-03-06T21:41:01","modified_gmt":"2011-03-06T21:41:01","slug":"design-and-implementation-of-mpeg-audio-layer-iii-decoder-using-graphics-processing-units","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=3121","title":{"rendered":"Design and implementation of MPEG audio layer III decoder using graphics processing units"},"content":{"rendered":"<p>This paper describes a new implemented method for the MPEG audio layer III (MP3) decoder. The proposed architecture is based on a graphic process unit (GPU) using CUDA environment, where it can effectively take advantage of modern GPU&#8217;s parallel computing power. The implemented system with this architecture employs a multi-thread model and memory optimization to process MP3 decoding in parallel, so it is significant to minimize the computational overhead. Experimental results on a GTX260+ graphics card showed that the proposed architecture is over five times faster than traditional MP3 library based on CPU.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper describes a new implemented method for the MPEG audio layer III (MP3) decoder. The proposed architecture is based on a graphic process unit (GPU) using CUDA environment, where it can effectively take advantage of modern GPU&#8217;s parallel computing power. The implemented system with this architecture employs a multi-thread model and memory optimization to [&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":[89,3,41],"tags":[14,20,253,1789],"class_list":["post-3121","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-paper","category-signal-processing","tag-cuda","tag-nvidia","tag-nvidia-geforce-gtx-260","tag-signal-processing"],"views":1852,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3121","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=3121"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3121\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3121"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3121"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3121"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}