Speeding Up Multi-Scalar Multiplication over Fixed Points Towards Efficient zkSNARKs

Guiwen Luo, Shihui Fu, G. Gong
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引用次数: 4

Abstract

The arithmetic of computing multiple scalar multiplications in an elliptic curve group then adding them together is called multi-scalar multiplication (MSM). MSM over fixed points dominates the time consumption in the pairing-based trusted setup zero-knowledge succinct non-interactive argument of knowledge (zkSNARK), thus for practical applications we would appreciate fast algorithms to compute it. This paper proposes a bucket set construction that can be utilized in the context of Pippenger’s bucket method to speed up MSM over fixed points with the help of precomputation. If instantiating the proposed construction over BLS12-381 curve, when computing n-scalar multiplications for n = 2e (10 ≤ e ≤ 21), theoretical analysis ndicates that the proposed construction saves more than 21% computational cost compared to Pippenger’s bucket method, and that it saves 2.6% to 9.6% computational cost compared to the most popular variant of Pippenger’s bucket method. Finally, our experimental result demonstrates the feasibility of accelerating the computation of MSM over fixed points using large precomputation tables as well as the effectiveness of our new construction.
面向高效zksnark的定点多标量乘法加速
在椭圆曲线群中计算多个标量乘法并将其相加的算法称为多标量乘法(MSM)。不动点上的MSM在基于配对的可信设置零知识简洁非交互式知识论证(zkSNARK)中占主导地位,因此对于实际应用,我们希望快速的算法来计算它。本文提出了一种桶集构造方法,可以在Pippenger桶法的背景下,借助预计算来加速不动点上的MSM。如果在BLS12-381曲线上实例化所提出的构造,当计算n = 2e(10≤e≤21)的n个标量乘法时,理论分析表明,所提出的构造比Pippenger的桶法节省21%以上的计算成本,比Pippenger的桶法最流行的变体节省2.6% ~ 9.6%的计算成本。最后,我们的实验结果证明了使用大型预计算表加速不动点上MSM计算的可行性以及我们的新结构的有效性。
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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