{"id":1926,"date":"2010-12-10T14:11:43","date_gmt":"2010-12-10T14:11:43","guid":{"rendered":"http:\/\/hgpu.org\/?p=1926"},"modified":"2010-12-10T14:11:43","modified_gmt":"2010-12-10T14:11:43","slug":"initial-experiences-porting-a-bioinformatics-application-to-a-graphics-processor","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=1926","title":{"rendered":"Initial Experiences Porting a Bioinformatics Application to a Graphics Processor"},"content":{"rendered":"<p>Bioinformatics applications are one of the most relevant and compute-demanding applications today. While normally these applications are executed on clusters or dedicated parallel systems, in this work we explore the use of an alternative architecture. We focus on exploiting the compute-intensive characteristics offered by the graphics processors (GPU) in order to accelerate a bioinformatics application. The GPU is a good match for these applications as it is an inexpensive, high-performance SIMD architecture.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Bioinformatics applications are one of the most relevant and compute-demanding applications today. While normally these applications are executed on clusters or dedicated parallel systems, in this work we explore the use of an alternative architecture. We focus on exploiting the compute-intensive characteristics offered by the graphics processors (GPU) in order to accelerate a bioinformatics application. [&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":[123,1781,218,20,903],"class_list":["post-1926","post","type-post","status-publish","format-standard","hentry","category-biology","category-paper","tag-bioinformatics","tag-biology","tag-brook","tag-nvidia","tag-nvidia-geforce-fx-5700"],"views":2099,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1926","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=1926"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1926\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1926"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1926"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1926"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}