{"id":12093,"date":"2014-05-20T00:14:54","date_gmt":"2014-05-19T21:14:54","guid":{"rendered":"http:\/\/hgpu.org\/?p=12093"},"modified":"2014-05-20T00:14:54","modified_gmt":"2014-05-19T21:14:54","slug":"parallel-approaches-to-edit-distance-and-approximate-string-matching","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=12093","title":{"rendered":"Parallel Approaches to Edit Distance and Approximate String Matching"},"content":{"rendered":"<p>In this paper, we explore approaches to parallelizing the edit distance problem and the related approximate string matching problem. The edit distance is a measure of the number of individual character insertions, deletions, and substitutions requried to transform one string into another string. In the canonical dynamic programming solution to the edit distance, a chain of dependencies renders parallelization extremely difficult; thus, we investigate several different approaches to resolve this issue.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper, we explore approaches to parallelizing the edit distance problem and the related approximate string matching problem. The edit distance is a measure of the number of individual character insertions, deletions, and substitutions requried to transform one string into another string. In the canonical dynamic programming solution to the edit distance, a chain [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,11,89,3],"tags":[1787,1782,14,20,379,206],"class_list":["post-12093","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-nvidia-cuda","category-paper","tag-algorithms","tag-computer-science","tag-cuda","tag-nvidia","tag-nvidia-geforce-gtx-480","tag-string-matching"],"views":2454,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12093","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=12093"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/12093\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=12093"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=12093"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=12093"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}