{"id":2191,"date":"2010-12-23T14:12:50","date_gmt":"2010-12-23T14:12:50","guid":{"rendered":"http:\/\/hgpu.org\/?p=2191"},"modified":"2010-12-23T14:12:50","modified_gmt":"2010-12-23T14:12:50","slug":"offloading-ids-computation-to-the-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2191","title":{"rendered":"Offloading IDS Computation to the GPU"},"content":{"rendered":"<p>Signature-matching intrusion detection systems can experience significant decreases in performance when the load on the IDS-host increases. We propose a solution that off-loads some of the computation performed by the IDS to the graphics processing unit (GPU). Modern GPUs are programmable, stream-processors capable of high-performance computing that in recent years have been used in non-graphical computing tasks. The major operation in a signature-matching IDS is matching values seen operation to known black-listed values, as such, our solution implements the string-matching on the GPU. The results show that as the CPU load on the IDS host system increases, PixelSnort&#8217;s performance is significantly more robust and is able to outperform conventional Snort by up to 40%.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Signature-matching intrusion detection systems can experience significant decreases in performance when the load on the IDS-host increases. We propose a solution that off-loads some of the computation performed by the IDS to the graphics processing unit (GPU). Modern GPUs are programmable, stream-processors capable of high-performance computing that in recent years have been used in non-graphical [&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":[11,3,287],"tags":[444,1782,20,301,182,1800],"class_list":["post-2191","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","category-security","tag-cg","tag-computer-science","tag-nvidia","tag-nvidia-geforce-6800-gt","tag-opengl","tag-security"],"views":2068,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2191","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=2191"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2191\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2191"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2191"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2191"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}