一种利用预处理改进RNS Montgomery幂的通用方法

F. Gandino, F. Lamberti, P. Montuschi, J. Bajard
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引用次数: 26

摘要

大整数模幂运算的硬件实现是数字算法中一个众所周知的课题。在RNS中使用Montgomery指数算法并执行必要的操作是实现并行和无携带实现的有效方法。Kawamura等人以及Bajard和Imbert提出了两种执行RNS Montgomery幂的有效方法。上述方法的主要区别在于实现基扩展所使用的算法。本文提出了一种改进的RNS Montgomery幂运算算法,其中几个乘法被移出主执行循环,并被一个有效的预处理阶段所取代,与最先进的方法相比,这大大节省了总体延迟。由于所提出的修改应适用于上述两种算法,因此具体讨论了两种版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A General Approach for Improving RNS Montgomery Exponentiation Using Pre-processing
The hardware implementation of modular exponentiation for very large integers is a well-known topic in digital arithmetic. An effective approach for obtaining parallel and carry-free implementations consists in using the Montgomery exponentiation algorithm and executing the necessary operations in RNS. Two efficient methods for performing the RNS Montgomery exponentiation have been proposed by Kawamura et al. and by Bajard and Imbert. The above approaches mainly differ in the algorithm used for implementing the base extension. This paper presents a modified RNS Montgomery exponentiation algorithm, where several multiplications are moved outside the main execution loop and replaced by an effective pre-processing stage producing a significant saving on the overall delay with respect to state-of-the-art approaches. Since the proposed modification should be applied to both of the above algorithms, two versions are specifically discussed.
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