Packet classification has been a fundamental processing pattern of modern networking devices. Today’s high-performance routers use specialized hardware for packet classification, but such solutions suffer from prohibitive cost, high power consumption, and poor extensibility. On the other hand, software-based routers offer the best flexibility, but could only deliver limited performance (<10Gbps). Recently, graphics processing units (GPUs) have been proved to be an efficient accelerator for software routers. In this work, we propose a GPU-based linear search framework for packet classification. The core of our framework is a metaprogramming technique that dramatically enhances the execution efficiency. Experimental results prove that our solution could outperform a CPU-based solution by a factor of 17, in terms of classification throughput. Our technique is scalable to large rule sets consisting of over 50K rules and thus provides a solid foundation for future applications of packet context inspection.\n<\/p>\n","protected":false},"excerpt":{"rendered":"
Packet classification has been a fundamental processing pattern of modern networking devices. Today’s high-performance routers use specialized hardware for packet classification, but such solutions suffer from prohibitive cost, high power consumption, and poor extensibility. On the other hand, software-based routers offer the best flexibility, but could only deliver limited performance (<\/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],"tags":[1782,475,476],"class_list":["post-4098","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-network-communications","tag-software-router"],"views":2038,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4098","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=4098"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4098\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4098"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4098"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4098"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}