{"title":"Analysis and acceleration of NTRU lattice-based cryptographic system","authors":"Tianyu Bai, Spencer Davis, Juanjuan Li, Hai Jiang","doi":"10.1109/SNPD.2014.6888686","DOIUrl":null,"url":null,"abstract":"Lattice based cryptography is attractive for its quantum computing resistance and efficient encryption/decryption process. However, the big data problem has perplexed lattice based cryptographic systems with the slow processing speed. This paper intends to analyze one of the major lattice-based cryptographic systems, Nth-degree truncated polynomial ring (NTRU), and accelerate its execution with Graphic Processing Unit (GPU) for acceptable processing performance. Three strategies, including single GPU with zero copy, single GPU with data transfer, and multi-GPU versions are proposed. GPU computing techniques such as stream and zero copy are applied to overlap the computation and communication for possible speedup. Experimental results have demonstrated the effectiveness of GPU acceleration of NTRU. As the number of involved devices increases, better NTRU performance will be achieved.","PeriodicalId":272932,"journal":{"name":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2014.6888686","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Lattice based cryptography is attractive for its quantum computing resistance and efficient encryption/decryption process. However, the big data problem has perplexed lattice based cryptographic systems with the slow processing speed. This paper intends to analyze one of the major lattice-based cryptographic systems, Nth-degree truncated polynomial ring (NTRU), and accelerate its execution with Graphic Processing Unit (GPU) for acceptable processing performance. Three strategies, including single GPU with zero copy, single GPU with data transfer, and multi-GPU versions are proposed. GPU computing techniques such as stream and zero copy are applied to overlap the computation and communication for possible speedup. Experimental results have demonstrated the effectiveness of GPU acceleration of NTRU. As the number of involved devices increases, better NTRU performance will be achieved.