CUDA is a platform developed by Nvidia for general purpose computing on Graphic Processing Unit to utilize the parallelism capabilities. Serpent encryption is considered to have high security margin as its advantage; however it lacks in speed as its disadvantage. We present a methodology for the transformation of CPU-based implementation of Serpent encryption algorithm (in C language) on CUDA to take advantage of CUDA’s parallel processing capability. The proposed methodology could be used to quickly port a CPU-based algorithm for a quick gain in performance. Further tweaking, as described in this paper through the use of a profiler, would further increase the performance gain. Result based on the integration of multiple block encryption in parallel shows throughput performance of up to 100 MB\/s or more than 7X performance gain.<\/p>\n","protected":false},"excerpt":{"rendered":"
CUDA is a platform developed by Nvidia for general purpose computing on Graphic Processing Unit to utilize the parallelism capabilities. Serpent encryption is considered to have high security margin as its advantage; however it lacks in speed as its disadvantage. We present a methodology for the transformation of CPU-based implementation of Serpent encryption algorithm (in […]<\/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":[11,89,3,287],"tags":[1782,14,20,253,1800],"class_list":["post-3744","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","category-security","tag-computer-science","tag-cuda","tag-nvidia","tag-nvidia-geforce-gtx-260","tag-security"],"views":1874,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3744","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=3744"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3744\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3744"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3744"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3744"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}