A Prediction-Based Scalable Design for Montgomery Modular Multiplication

Abstract

Modular multiplication is a basic operation in public key cryptosystems, like RSA and elliptic curve cryptography (ECC). There are many algorithms to speed up its calculation. Among them, Montgomery algorithm is the most efficient method for avoiding expensive divisions. Recently, due to the increasing use of diverse embedded systems, variable precision modular multiplications with scalable architectures gain more and more attentions. In this paper, we propose a new word-based implementation of Montgomery modular multiplication. A predict policy is incorporated with a scalable architecture to reduce area cost and time latency. Compared with other scalable designs, our area-time product is the best among all, with little memory overhead. Keywords—Montgomery modular multiplication, wordbased version of Montgomery algorithm, scalable architecture.