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ZKPU: Zero-Knowledge Processing Unit for Heterogeneous Workloads
Jonathan Ku, Changchun Zhou, Jiawen Wu, Sangouk Jeon, Cong Guo, Yuzhe Fu, Bowen Duan, Dongsuk Jeon, JV Rajendran, Yiran Chen, Hai Li

ZKPU: Zero-Knowledge Processing Unit for Heterogeneous Workloads

Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

Zero-knowledge proofs (ZKPs) have become a fundamental building block for privacy-preserving computation, blockchain systems, and verifiable machine learning. Modern ZKP protocols span two distinct families: curve-based protocols, which rely on large finite-field arithmetic, and hash-based protocols, which operate over native 64-bit fields. Existing hardware accelerators are specialized for one protocol family because they are built on operand-scanning Montgomery multiplication, resulting in fixed-width datapaths, poor utilization across heterogeneous operand widths, and limited scalability. This paper presents \emph{ZKPU}, a Zero-Knowledge Processing Unit for heterogeneous ZKP workloads. ZKPU introduces a new compute paradigm by co-designing finely integrated product scanning (FIPS) Montgomery multiplication with a reconfigurable Twin Systolic Fabric (TSF), enabling modular multiplication at arbitrary widths in 64-bit increments. Combined with a fine-grained Deque buffer, on-chip twiddle-factor generator, and memory-efficient MSM preprocessing strategy, ZKPU provides a unified architecture for both curve-based and hash-based protocols. Evaluation using Groth16 and Plonky2 shows that ZKPU achieves up to $144\times$ speedup for NTT, $13.6\times$ for MSM, and approximately $7.2\times$ end-to-end application speedup over state-of-the-art accelerators, while being the first architecture to efficiently support both protocol families on a single reconfigurable hardware platform.

Indexed from repository: arXiv (arxiv.org)
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Document Information

Document Title ZKPU: Zero-Knowledge Processing Unit for Heterogeneous Workloads
Author / Organization Jonathan Ku, Changchun Zhou, Jiawen Wu, Sangouk Jeon, Cong Guo, Yuzhe Fu, Bowen Duan, Dongsuk Jeon, JV Rajendran, Yiran Chen, Hai Li
Subject & Discipline cs.AR
Categories Science & Mathematics
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-271364
Original Source Link Visit Source Page on arxiv.org »