{"id":18364,"date":"2018-07-05T09:05:57","date_gmt":"2018-07-05T06:05:57","guid":{"rendered":"https:\/\/hgpu.org\/?p=18364"},"modified":"2018-07-05T09:05:57","modified_gmt":"2018-07-05T06:05:57","slug":"evaluating-the-efficiency-of-cpus-gpus-and-fpgas-on-a-near-duplicate-document-detection-via-opencl","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=18364","title":{"rendered":"Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCL"},"content":{"rendered":"<p>Discovering identical or near-identical items is urgently important in many applications such as Web crawling since it drastically reduces the text processing costs. Simhash is a widely used technique, able to attribute a bit-string identity to a text, such that similar texts have similar identities. In this study, a real-time solution for a simhash calculation in OpenCL is presented. We also show how it can be utilized by multi-CPUs, GPUs and FPGAs. As a result we indicate that the bottom line computation realized on the FPGA through OpenCL provides significant power advantages.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Discovering identical or near-identical items is urgently important in many applications such as Web crawling since it drastically reduces the text processing costs. Simhash is a widely used technique, able to attribute a bit-string identity to a text, such that similar texts have similar identities. In this study, a real-time solution for a simhash calculation [&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":[11,90,3],"tags":[1782,377,1025,1815,1793],"class_list":["post-18364","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-computer-science","tag-fpga","tag-machine-learning","tag-nlp","tag-opencl"],"views":2056,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/18364","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=18364"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/18364\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=18364"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=18364"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=18364"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}