Yoimiya: A Scalable Framework for Optimal Resource Utilization in ZK-SNARK Systems

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Hauptverfasser: Ye, Zheming, Qi, Xiaodong, Zhang, Zhao, Jin, Cheqing
Format: Preprint
Veröffentlicht: 2025
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author Ye, Zheming
Qi, Xiaodong
Zhang, Zhao
Jin, Cheqing
author_facet Ye, Zheming
Qi, Xiaodong
Zhang, Zhao
Jin, Cheqing
contents With the widespread adoption of Zero-Knowledge Proof systems, particularly ZK-SNARK, the efficiency of proof generation, encompassing both the witness generation and proof computation phases, has become a significant concern. While substantial efforts have successfully accelerated proof computation, progress in optimizing witness generation remains limited, which inevitably hampers overall efficiency. In this paper, we propose Yoimiya, a scalable framework with pipeline, to optimize the efficiency in ZK-SNARK systems. First, Yoimiya introduces an automatic circuit partitioning algorithm that divides large circuits of ZK-SNARK into smaller subcircuits, the minimal computing units with smaller memory requirement, allowing parallel processing on multiple units. Second, Yoimiya decouples witness generation from proof computation, and achieves simultaneous executions over units from multiple circuits. Moreover, Yoimiya enables each phase scalable separately by configuring the resource distribution to make the time costs of the two phases aligned, maximizing the resource utilization. Experimental results confirmed that our framework effectively improves the resource utilization and proof generation speed.
format Preprint
id arxiv_https___arxiv_org_abs_2502_18288
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Yoimiya: A Scalable Framework for Optimal Resource Utilization in ZK-SNARK Systems
Ye, Zheming
Qi, Xiaodong
Zhang, Zhao
Jin, Cheqing
Cryptography and Security
Emerging Technologies
With the widespread adoption of Zero-Knowledge Proof systems, particularly ZK-SNARK, the efficiency of proof generation, encompassing both the witness generation and proof computation phases, has become a significant concern. While substantial efforts have successfully accelerated proof computation, progress in optimizing witness generation remains limited, which inevitably hampers overall efficiency. In this paper, we propose Yoimiya, a scalable framework with pipeline, to optimize the efficiency in ZK-SNARK systems. First, Yoimiya introduces an automatic circuit partitioning algorithm that divides large circuits of ZK-SNARK into smaller subcircuits, the minimal computing units with smaller memory requirement, allowing parallel processing on multiple units. Second, Yoimiya decouples witness generation from proof computation, and achieves simultaneous executions over units from multiple circuits. Moreover, Yoimiya enables each phase scalable separately by configuring the resource distribution to make the time costs of the two phases aligned, maximizing the resource utilization. Experimental results confirmed that our framework effectively improves the resource utilization and proof generation speed.
title Yoimiya: A Scalable Framework for Optimal Resource Utilization in ZK-SNARK Systems
topic Cryptography and Security
Emerging Technologies
url https://arxiv.org/abs/2502.18288