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论文摘要

GPU结构的椭圆曲线加密流化技术

Streaming Elliptic Curve Cryptography for Many-core GPU

作者:甘新标();沈立();王志英()

Author:Gan Xinbiao();Shen Li();Wang Zhiying()

收稿日期:2010-03-25          年卷(期)页码:2011,43(2):98-102

期刊名称:工程科学与技术

Journal Name:Advanced Engineering Sciences

关键字:GPU;ECC;流化并行;优化; CUDA

Key words:GPU;ECC;streaming;optimization;CUDA

基金项目:重点基础研究发展计划;国家自然科学基金;国防科技大学优秀研究生创新资助

中文摘要

针对椭圆曲线加密系统的加密速度不能满足实时性要求的现状,提出利用众核GPU强大的计算资源和有效的存储带宽来优化加速椭圆曲线加密机制(Elliptic Curve Cryptography, ECC),主要方法包括开发并行多线程来流化ECC以及利用GPU存储层次进行优化等关键技术。实验结果显示,在支持计算统一设备架构(Computing Unified Device Architecture, CUDA)的GPU上流化实现的ECC原型系统与优化的CPU实现相比可获得高达66×的加速度比。另外,针对ECC的流化并行及优化技术可作为一般方法推广至其它流体系结构。

英文摘要

With embarrass of the weakness in real-time requirements of ECC (Elliptic Curve Cryptograph). Streaming ECC with optimization was proposed, including streaming ECC for parallelization using thousands of threads as well as stream optimization with best utilization of memory hierarchy of CUDA-enable GPU. Experimental results show that prototype of ECC implemented using CUDA (Computing Unified Device Architecture) on NVIDIA’s GTX280 could achieve as high as 66×speedup than CPU counterpart available. Furthermore, above proposed techniques including streaming for parallelization and optimizations with memory hierarchy could be generalized for other streaming architectures.

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