{"title":"基于CUDA的蛇形加密算法实现","authors":"Anas Mohd Nazlee, F. Hussin, N. Ali","doi":"10.1109/SCORED.2009.5443190","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":443287,"journal":{"name":"2009 IEEE Student Conference on Research and Development (SCOReD)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Serpent encryption algorithm implementation on Compute Unified Device Architecture (CUDA)\",\"authors\":\"Anas Mohd Nazlee, F. Hussin, N. Ali\",\"doi\":\"10.1109/SCORED.2009.5443190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":443287,\"journal\":{\"name\":\"2009 IEEE Student Conference on Research and Development (SCOReD)\",\"volume\":\"89 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Student Conference on Research and Development (SCOReD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCORED.2009.5443190\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Student Conference on Research and Development (SCOReD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCORED.2009.5443190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Serpent encryption algorithm implementation on Compute Unified Device Architecture (CUDA)
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.