具有可变字长加速器的有限域算法软核处理器

Aiko Iwasaki, Keisuke Dohi, Yuichiro Shibata, K. Oguri, Ryuichi Harasawa
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引用次数: 2

摘要

本文提出了一种软核加速架构的实现和评价,以加快椭圆曲线密码系统中GF(2m)算法的约简过程。在这种体系结构中,当在FPGA上配置该体系结构时,可以自定义加速器的字长。针对GF(2m)上的约简处理操作次数受不可约多项式和字长影响的事实,我们建议根据给定的不可约多项式为加速器采用非常规的字长,并实现基于mips的软核处理器和可变字长加速器。通过几个多项式的评估,结果表明,即使考虑到改变字长导致的20.4%的最大频率下降,与32位字长相比,性能提高了10.2倍。使用非常规字长的优势也被展示出来,表明这种方法在低功耗ECC系统中的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A soft-core processor for finite field arithmetic with a variable word size accelerator
This paper presents implementation and evaluation of an accelerator architecture for soft-cores to speed up reduction process for the arithmetic on GF(2m) used in Elliptic Curve Cryptography (ECC) systems. In this architecture, the word size of the accelerator can be customized when the architecture is configured on an FPGA. Focusing on the fact that the number of the reduction processing operations on GF(2m) is affected by the irreducible polynomial and the word size, we propose to employ an unconventional word size for the accelerator depending on a given irreducible polynomial and implement a MIPS-based soft-core processor coupled with a variable-word size accelerator. As a result of evaluation with several polynomials, it was shown that the performance improvement of up to 10.2 times was obtained compared to the 32-bit word size, even taking into account the maximum frequency degradation of 20.4% caused by changing the word size. The advantage of using unconventional word sizes was also shown, suggesting the promise of this approach for low-power ECC systems.
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