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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 10
3059-3067

PreNTT: parallel acceleration method for number theory transformation calculations for zk-SNARK

Ding Dong1a
Li Zhengquan1a,2
Chai Zhilei1b
1. a. School of Internet of Things Engineering, b. School of Artificial Intelligence & Computer Science, Jiangnan University, Wuxi Jiangsu 214122, China
2. State Key Laboratory of Networking & Switching Technology, Beijing University of Posts & Telecommunications, Beijing 100876, China
DOI: 10.19734/j.issn.1001-3695.2024.03.0054

Abstract

Zero-knowledge succinct non-interactive proofs(zk-SNARK) have found extensive applications in various fields, including cryptocurrencies, due to their swift and efficient proof verification process. However, the computational intensity of the proof generation process poses a significant challenge, particularly at the number theoretic transform(NTT) stage. This paper proposed a GPU-based acceleration method for NTT computations, named PreNTT, to address this bottleneck. The method employed precomputation and optimization of twiddle factor powers to reduce the parallel computation overhead in NTT. It also introduced dynamic precomputation to enhance the efficiency of these computations. The algorithm made use of dynamic adaptive kernel scheduling, which allocated GPU resources on-chip according to the NTT input size, thereby boosting the computational efficiency for large-scale tasks. Additionally, the approach combined external global data shuffling with internal local data shuffling to avoid memory access conflicts. The use of CUDA multi-stream technology allowed for effective concealment of precomputation times during data transfer and computation processes. Experimental results indicate that the zk-SNARK system utilizing PreNTT achieves a speed-up ratio ranging from 1.7x to 9x in NTT module running times compared to Bellperson, the industry-leading system. PreNTT effectively increases the parallelism of the NTT algorithm and reduces the computational overhead in zk-SNARK operations.

Foundation Support

国家自然科学基金资助项目(61972180)
北京邮电大学网络与交换技术全国重点实验室开放课题资助项目(SKLNST-2023-1-13)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.03.0054
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 10
Section: System Development & Application
Pages: 3059-3067
Serial Number: 1001-3695(2024)10-025-3059-09

Publish History

[2024-07-05] Accepted Paper
[2024-10-05] Printed Article

Cite This Article

丁冬, 李正权, 柴志雷. PreNTT：面向zk-SNARK的数论变换计算并行加速方法 [J]. 计算机应用研究, 2024, 41 (10): 3059-3067. (Ding Dong, Li Zhengquan, Chai Zhilei. PreNTT: parallel acceleration method for number theory transformation calculations for zk-SNARK [J]. Application Research of Computers, 2024, 41 (10): 3059-3067. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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