BatchZK: A Fully Pipelined GPU-Accelerated System for Batch Generation of Zero-Knowledge Proofs

Zero-knowledge proof (ZKP) is a cryptographic primitive that enables one party to prove the validity of a statement to other parties without disclosing any secret information. With its widespread adoption in applications such as blockchain and verifiable machine learning, the demand for generating zero-knowledge proofs has increased dramatically. In recent years, considerable efforts have been directed toward developing GPU-accelerated systems for proof generation. However, these previous systems only explored efficiently generating a single proof by reducing latency rather than batch generation to provide high throughput.

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Publication Details

Published
2025-02-06
DOI
https://doi.org/10.1145/3669940.3707270
Citations
3
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
3.83
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article

BatchZK: A Fully Pipelined GPU-Accelerated System for Batch Generation of Zero-Knowledge Proofs

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3 citations
Advanced Neural Network Applications
3.83
article

BatchZK: A Fully Pipelined GPU-Accelerated System for Batch Generation of Zero-Knowledge Proofs

Zonghui Wang, Tao Lu, Xiaohang Wang, Yicheng Chen, Wenzhi Chen, J. Zhang
article en
3 citations

Abstract

Zero-knowledge proof (ZKP) is a cryptographic primitive that enables one party to prove the validity of a statement to other parties without disclosing any secret information. With its widespread adoption in applications such as blockchain and verifiable machine learning, the demand for generating zero-knowledge proofs has increased dramatically. In recent years, considerable efforts have been directed toward developing GPU-accelerated systems for proof generation. However, these previous systems only explored efficiently generating a single proof by reducing latency rather than batch generation to provide high throughput.

National University of Singapore (SG), Zhejiang University (CN)
Openalex Percentile: Top 8%
Advanced Neural Network Applications
3.83
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