{"id":5746,"date":"2011-10-01T10:31:44","date_gmt":"2011-10-01T07:31:44","guid":{"rendered":"http:\/\/hgpu.org\/?p=5746"},"modified":"2011-10-01T10:31:44","modified_gmt":"2011-10-01T07:31:44","slug":"large-scale-dna-sequence-alignment-and-kernel-method-implemented-with-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5746","title":{"rendered":"Large Scale DNA Sequence Alignment and Kernel Method Implemented with GPUs"},"content":{"rendered":"<p>Large Scale DNA sequence alignment and Kernel method in molecular biology play critical roles in bioinformatics. Both of which are successfully implemented on the brook+ platform with AMD&#8217;s GPUs. Aiming at the characters of graphical stream processors, we propose internal and external approach cooperatively to promote the performance of the two algorithms. The experiments show that the performance of 2D graph-based DNA sequence alignment based on GPUs is more than 25x faster than that of a single CPU-based one, and the parallel kernel matrix computing runs 7x faster on the same platform due to the write-back bottleneck of graph memory which simultaneously reveals the limitation of GPUs computing.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Large Scale DNA sequence alignment and Kernel method in molecular biology play critical roles in bioinformatics. Both of which are successfully implemented on the brook+ platform with AMD&#8217;s GPUs. Aiming at the characters of graphical stream processors, we propose internal and external approach cooperatively to promote the performance of the two algorithms. The experiments show [&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":[36,10,3],"tags":[1787,7,255,123,1781,218,209],"class_list":["post-5746","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-biology","category-paper","tag-algorithms","tag-ati","tag-ati-radeon-hd-4870","tag-bioinformatics","tag-biology","tag-brook","tag-sequence-alignment"],"views":2509,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5746","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=5746"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5746\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5746"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5746"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5746"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}