法利克基于 FPGA 的零知识证明多乘法加速器

IF 3.6 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Yongkui Yang;Zhenyan Lu;Jingwei Zeng;Xingguo Liu;Xuehai Qian;Zhibin Yu
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引用次数: 0

摘要

本文提出了一种基于 FPGA 的新型加速器 Falic,用于加速多标量乘法 (MSM),这是 zk-SNARK 证明生成过程中最耗时的阶段。Falic 创新了三种技术。首先,它利用全局异步局部同步(GALS)策略构建了多个小型轻量级 MSM 内核,以并行处理标量向量和点向量不同部分的独立内积计算。其次,每个 MSM 内核仅包含一个大整数模块乘法器 (LIMM),该乘法器被复用以执行 MSM 期间生成的点加法 (PADD)。我们通过批处理适当数量的 PADD 和选择具有适当并行度的 PADD 计算图,在吞吐量和硬件成本之间取得平衡。最后,简单的缓存结构实现了计算的重复使用,从而进一步提高了性能。我们在两种具有不同硬件资源的 FPGA(即 Xilinx U200 和 Xilinx U250)上实现了 Falic。与之前基于 FPGA 的加速器相比,Falic 将 MSM 吞吐量提高了 3.9 美元(boldsymbol{\times}$)。实验结果还显示,与 RTX 2080Ti GPU 相比,Falic 实现了高达 1.62 美元的吞吐量加速,并节省了高达 8.5 美元的能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Falic: An FPGA-Based Multi-Scalar Multiplication Accelerator for Zero-Knowledge Proof
In this paper, we propose Falic, a novel FPGA-based accelerator to accelerate multi-scalar multiplication (MSM), the most time-consuming phase of zk-SNARK proof generation. Falic innovates three techniques. First, it leverages globally asynchronous locally synchronous (GALS) strategy to build multiple small and lightweight MSM cores to parallelize the independent inner product computation on different portions of the scalar vector and point vector. Second, each MSM core contains just one large-integer modular multiplier (LIMM) that is multiplexed to perform the point additions (PADDs) generated during MSM. We strike a balance between the throughput and hardware cost by batching the appropriate number of PADDs and selecting the computation graph of PADD with proper parallelism degree. Finally, the performance is further improved by a simple cache structure that enables the computation reuse. We implement Falic on two different FPGAs with different hardware resources, i.e., the Xilinx U200 and Xilinx U250. Compared to the prior FPGA-based accelerator, Falic improves the MSM throughput by $3.9\boldsymbol{\times}$ . Experimental results also show that Falic achieves a throughput speedup of up to $1.62\boldsymbol{\times}$ and saves as much as $8.5\boldsymbol{\times}$ energy compared to an RTX 2080Ti GPU.
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来源期刊
IEEE Transactions on Computers
IEEE Transactions on Computers 工程技术-工程:电子与电气
CiteScore
6.60
自引率
5.40%
发文量
199
审稿时长
6.0 months
期刊介绍: The IEEE Transactions on Computers is a monthly publication with a wide distribution to researchers, developers, technical managers, and educators in the computer field. It publishes papers on research in areas of current interest to the readers. These areas include, but are not limited to, the following: a) computer organizations and architectures; b) operating systems, software systems, and communication protocols; c) real-time systems and embedded systems; d) digital devices, computer components, and interconnection networks; e) specification, design, prototyping, and testing methods and tools; f) performance, fault tolerance, reliability, security, and testability; g) case studies and experimental and theoretical evaluations; and h) new and important applications and trends.
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