{"id":4762,"date":"2011-07-14T15:48:05","date_gmt":"2011-07-14T12:48:05","guid":{"rendered":"http:\/\/hgpu.org\/?p=4762"},"modified":"2011-07-14T15:48:05","modified_gmt":"2011-07-14T12:48:05","slug":"fast-parallel-algorithm-for-audio-content-retrieval-on-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4762","title":{"rendered":"Fast parallel algorithm for audio content retrieval on GPUs"},"content":{"rendered":"<p>The search techniques audio content MIR (music information retrieval) face two major challenges: the robustness of the algorithm and the speed of this operation. In this article proposes a model of fast algorithm for the extraction of audio data by the fingerprinting technique, which is implemented on a CPU-based platform and then parallelized to run on a graphics hardware (GPU). Tests on GPU determined a success rate close to 100% and response times approximately 2 times lower than those obtained with a PC workstation, allowing searches of up to 65 commercial in real-time.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The search techniques audio content MIR (music information retrieval) face two major challenges: the robustness of the algorithm and the speed of this operation. In this article proposes a model of fast algorithm for the extraction of audio data by the fingerprinting technique, which is implemented on a CPU-based platform and then parallelized to run [&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":[36,3,41],"tags":[1787,607,1789],"class_list":["post-4762","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-paper","category-signal-processing","tag-algorithms","tag-information-retrieval","tag-signal-processing"],"views":2055,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4762","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=4762"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4762\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4762"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4762"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4762"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}