{"id":5036,"date":"2011-08-07T12:13:56","date_gmt":"2011-08-07T09:13:56","guid":{"rendered":"http:\/\/hgpu.org\/?p=5036"},"modified":"2011-08-07T12:13:56","modified_gmt":"2011-08-07T09:13:56","slug":"hardware-accelerators-for-biocomputing-a-survey","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5036","title":{"rendered":"Hardware accelerators for biocomputing: A survey"},"content":{"rendered":"<p>Computing research has become a vital cog in the machinery required to drive biological discovery. Computing has made possible significant achievements over the last decade, especially in the genomics sector. An emerging area is the investigation of hardware accelerators for speeding up the massive scale of computation needed in large-scale biocomputing applications. Various hardware platforms, such as FPGA, Graphics Processing Unit (GPU), the Cell Broadband Engine (CBE) and multi-core processors are being explored. In this paper, we present a survey of hardware accelerators for biocomputing by choosing a representative set of each.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Computing research has become a vital cog in the machinery required to drive biological discovery. Computing has made possible significant achievements over the last decade, especially in the genomics sector. An emerging area is the investigation of hardware accelerators for speeding up the massive scale of computation needed in large-scale biocomputing applications. Various hardware platforms, [&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":[10,89,3],"tags":[1781,545,14,377,112,20,247,67,31,209],"class_list":["post-5036","post","type-post","status-publish","format-standard","hentry","category-biology","category-nvidia-cuda","category-paper","tag-biology","tag-cell-processor","tag-cuda","tag-fpga","tag-molecular-dynamics","tag-nvidia","tag-nvidia-geforce-7800-gtx","tag-performance","tag-review","tag-sequence-alignment"],"views":3270,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5036","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=5036"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5036\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5036"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5036"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5036"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}