GZKP: A GPU Accelerated Zero-Knowledge Proof System

  • Weiliang Ma
  • , Qian Xiong
  • , Xuanhua Shi*
  • , Xiaosong Ma
  • , Hai Jin
  • , Haozhao Kuang
  • , Mingyu Gao
  • , Ye Zhang
  • , Haichen Shen
  • , Weifang Hu
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

35 Citations (Scopus)

Abstract

Zero-knowledge proof (ZKP) is a cryptographic protocol that allows one party to prove the correctness of a statement to another party without revealing any information beyond the correctness of the statement itself. It guarantees computation integrity and confidentiality, and is therefore increasingly adopted in industry for a variety of privacy-preserving applications, such as verifiable outsource computing and digital currency. A significant obstacle in using ZKP for online applications is the performance overhead of its proof generation. We develop GZKP, a GPU accelerated zero-knowledge proof system that supports different levels of security requirements and brings significant speedup toward making ZKP truly usable. For polynomial computation over a large finite field, GZKP promotes a cache-friendly memory access pattern while eliminating the costly external shuffle in existing solutions. For multi-scalar multiplication, GZKP adopts a new parallelization strategy, which aggressively combines integer elliptic curve point operations and exploits fine-grained task parallelism with load balancing for sparse integer distribution. GZKP outperforms the state-of-the-art ZKP systems by an order of magnitude, achieving up to 48.1× and 17.6× speedup with standard cryptographic benchmarks and a real-world application workload, respectively.

Original languageEnglish
Title of host publicationASPLOS 2023 - Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
EditorsTor M. Aamodt, Natalie Enright Jerger, Michael Swift
PublisherAssociation for Computing Machinery
Pages340-353
Number of pages14
ISBN (Electronic)9781450399166
DOIs
Publication statusPublished - 27 Jan 2023
Event28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2023 - Vancouver, Canada
Duration: 25 Mar 202329 Mar 2023

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
Volume2

Conference

Conference28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2023
Country/TerritoryCanada
CityVancouver
Period25/03/2329/03/23

Keywords

  • GPU acceleration
  • Zero-knowledge proof

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