GPU-acceleration of blowfish cryptographic algorithm

Kapil Earanky, H. Elmiligi, Musfiq Rahman
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引用次数: 2

Abstract

The demand for fast and secure cryptographic encryption techniques has been growing over the recent years. The introduction of the CUDA programming framework by NVIDIA allowed utilizing GPUs for general purpose computing. The use of GPUs in the cryptography domain has become quite popular ever since. In this paper, we present a CUDA implementation of the blowfish encryption algorithm. The algorithm has been designed to make use of the unified memory model introduced as a part of CUDA 6. Experimental results show that the unified implementation of the blowfish algorithm performs better than an efficient CPU implementation by a factor of 62X and performs twice better than a non-unified CUDA implementation of the algorithm. We also present possible solutions to achieve an optimal configuration for the target GPU to get the best performance.
河豚密码算法的gpu加速
近年来,对快速、安全的加密技术的需求不断增长。NVIDIA引入的CUDA编程框架允许利用gpu进行通用计算。从那时起,gpu在密码学领域的使用就变得相当流行。在本文中,我们提出了河豚加密算法的CUDA实现。该算法被设计为利用作为CUDA 6的一部分引入的统一内存模型。实验结果表明,河豚算法的统一实现比高效的CPU实现的性能好62倍,比非统一的CUDA实现的算法性能好2倍。我们还提出了可能的解决方案,以实现目标GPU的最佳配置,以获得最佳性能。
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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