GZKP: A GPU Accelerated Zero-Knowledge Proof System

被引:10
作者
Ma, Weiliang [1 ]
Xiong, Qian [1 ]
Shi, Xuanhua [1 ]
Ma, Xiaosong [2 ]
Jin, Hai [1 ]
Kuang, Haozhao [1 ]
Gao, Mingyu [3 ]
Zhang, Ye [4 ]
Shen, Haichen [4 ]
Hu, Weifang [1 ]
机构
[1] Huazhong Univ Sci & Technol, Natl Engn Res Ctr Big Data Technol & Syst, Serv Comp Technol & Syst Lab, Sch Comp Sci & Technol,Cluster & Grid Comp Lab, Wuhan, Hubei, Peoples R China
[2] Hamad Bin Khalifa Univ, Doha, Qatar
[3] Tsinghua Univ, Beijing, Peoples R China
[4] Scroll Fdn, Victoria, Beau Vallon, Seychelles
来源
PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON ARCHITECTURAL SUPPORT FOR PROGRAMMING LANGUAGES AND OPERATING SYSTEMS, VOL 2, ASPLOS 2023 | 2023年
基金
国家重点研发计划;
关键词
zero-knowledge proof; GPU acceleration;
D O I
10.1145/3575693.3575711
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 48.1x and 17.6x speedup with standard cryptographic benchmarks and a real-world application workload, respectively.
引用
收藏
页码:340 / 353
页数:14
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