A Matrix Decomposition Method for Odd-Type Gaussian Normal Basis Multiplication

Kittiphon Phalakarn, A. Surarerks
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Abstract

Normal basis is used in many applications because of the efficiency of the implementation. However, most space complexity reduction techniques for binary field multiplier are applicable for only optimal normal basis or Gaussian normal basis of even type. There are 187 binary fields GF 2k for k from 2 to 1,000 that use odd-type Gaussian normal basis. This paper presents a method to reduce the space complexity of odd-type Gaussian normal basis multipliers over binary field GF 2k. The idea is adapted from the matrix decomposition method for optimal normal basis. The result shows that our space complexity reduction method can reduce the number of XOR gates used in the implementation comparing to previous works with a small trade-off in critical path delay.
奇型高斯正态基乘法的矩阵分解方法
由于正常基的实现效率高,在很多应用中都采用了正常基。然而,大多数二元域乘法器的空间复杂度降低技术只适用于最优正态基或偶型高斯正态基。对于k从2到1000,有187个使用奇型高斯正态基的二进制字段gf2k。本文提出了一种降低二元域gf2k上奇型高斯正态基乘法器空间复杂度的方法。该思想借鉴了求最优正态基的矩阵分解方法。结果表明,与以前的方法相比,我们的空间复杂度降低方法可以减少实现中使用的异或门的数量,并且在关键路径延迟方面有很小的权衡。
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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