{"id":4350,"date":"2011-06-15T13:37:28","date_gmt":"2011-06-15T13:37:28","guid":{"rendered":"http:\/\/hgpu.org\/?p=4350"},"modified":"2011-06-15T13:37:28","modified_gmt":"2011-06-15T13:37:28","slug":"the-accelerating-implementation-of-blast-with-stream-processor","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4350","title":{"rendered":"The accelerating implementation of BLAST with stream processor"},"content":{"rendered":"<p>Sequence alignment is one of the most fundamental and important operation in bioinformatics. Through sequence alignment, we can find the sequence&#8217;s information of function, structure and evolution. BLAST is one of the most popular algorithms in the field of sequence alignment. In this paper, we have designed a GPU-based parallel BLAST algorithm and implemented it on the brook+ platform. The main task is to parallel the construction of words lists procedure and the match-expansion procedure. As for match-expansion procedure, we designed two ways to parallelize it including internal parallelism and mixed parallelism. According to results of experiments based on AMD&#8217;s HD4850, we got more than 3x gains on parallel implementing the procedure of construction of words list and the implementation of internal parallelism respectively compared with CPU-based implementations. Besides, we got more than 4x gains for mixed parallelism as well. Furthermore, the experiments verified that the procedure of reading and writing data through PCI-E was the bottleneck of AMD&#8217;s GPU applications.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Sequence alignment is one of the most fundamental and important operation in bioinformatics. Through sequence alignment, we can find the sequence&#8217;s information of function, structure and evolution. BLAST is one of the most popular algorithms in the field of sequence alignment. In this paper, we have designed a GPU-based parallel BLAST algorithm and implemented it [&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":[10,3],"tags":[7,417,123,1781,878,218,209],"class_list":["post-4350","post","type-post","status-publish","format-standard","hentry","category-biology","category-paper","tag-ati","tag-ati-radeon-hd-4850","tag-bioinformatics","tag-biology","tag-blast","tag-brook","tag-sequence-alignment"],"views":2428,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4350","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=4350"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4350\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4350"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4350"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4350"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}