SC22 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Technical Papers Archive

Accelerating Elliptic Curve Digital Signature Algorithms on GPUs

Authors: Zonghao Feng and Qipeng Xie (Hong Kong University of Science and Technology); Qiong Luo (Hong Kong University of Science and Technology; Hong Kong University of Science and Technology, Guangzhou); and Yujie Chen, Haoxuan Li, Huizhong Li, and Qiang Yan (WeBank, China)

Abstract: The Elliptic Curve Digital Signature Algorithm (ECDSA) is an essential building block of various cryptographic protocols. In particular, most blockchain systems adopt it to ensure transaction integrity. However, due to its high computational intensity, ECDSA is often the performance bottleneck in blockchain transaction processing. Recent work has accelerated ECDSA algorithms on the CPU; in contrast, success has been limited on the GPU, which has great potential for parallelization but is challenging for implementing elliptic curve functions. In this paper, we propose RapidEC, a GPU-based ECDSA implementation for SM2, a popular elliptic curve. Specifically, we design architecture-aware parallel primitives for elliptic curve point operations, and parallelize the processing of a single SM2 request as well as batches of requests. Consequently, our GPU-based RapidEC outperformed the state-of-the-art CPU-based algorithm by orders of magnitude. Additionally, our GPU-based modular arithmetic functions as well as point operation primitives can be applied to other computation tasks.

Presentation: file

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