Accelerating NTRU Encryption with Graphics Processing Units

Tianyu Bai, Spencer Davis, Juanjuan Li, Ying Gu, Hai Jiang
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引用次数: 3

Abstract

Lattice based cryptography is attractive for its quantum computing resistance and efficient encryption/decryption process. However, the Big Data issue has perplexed most lattice based cryptographic systems since the overall processing is slowed down too much. 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 speed. Three strategies, including single GPU with zero copy, single GPU with data transfer, and multi-GPU versions are proposed for performance comparison. GPU computing techniques such as stream and zero copy are applied to overlap computations and communications 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.
加速NTRU加密与图形处理单元
基于点阵的密码学以其抗量子计算能力和高效的加解密过程而备受关注。然而,大数据问题一直困扰着大多数基于点阵的密码系统,因为整体处理速度太慢了。本文旨在分析主要的基于格的密码系统之一,n度截断多项式环(NTRU),并利用图形处理单元(GPU)加速其执行,以获得可接受的处理速度。提出了单GPU零拷贝、单GPU带数据传输和多GPU版本三种策略进行性能比较。GPU计算技术,如流和零复制应用于重叠计算和通信,以可能的加速。实验结果证明了GPU加速NTRU的有效性。随着所涉及设备数量的增加,NTRU的性能将得到提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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