ZK-Flex: A Flexible and Scalable Framework for Accelerating Zero-Knowledge Proofs

2026-06-01

AI Summary

Zero-knowledge proof generation is computationally intensive, and existing hardware accelerators suffer from limited precision scalability, low algorithmic flexibility, and insufficient resource efficiency when handling multi-precision modular multiplication and dynamic switching between polynomial and elliptic curve operations. This work proposes ZK-Flex, a hardware-software co-designed framework that integrates hardware-aware optimization algorithms for polynomials and elliptic curves. It introduces TCore, a multi-precision arithmetic core based on Toom-Cook multiplication, coupled with a flexible on-chip network and a linked-list-based memory management scheme to significantly enhance parallelism and resource utilization. Evaluated on representative zero-knowledge benchmarks, ZK-Flex achieves 5–11× speedup over state-of-the-art solutions and improves area efficiency by up to 3.8×.

Abstract

Zero-knowledge proofs (ZKP) allows a prover to convince a verifier of computational correctness without revealing private data, ensuring both privacy and verifiability. However, proof generation is highly compute-intensive, dominated by polynomial (POLY) and elliptic-curve (EC) operations. These workloads pose two key challenges for hardware acceleration: (1) efficiently supporting diverse large-precision modular multiplications, and (2) maintaining high utilization across workloads that dynamically shift between POLY and EC stages. Existing reconfigurable accelerators address these issues only partially, remaining limited in precision scalability, algorithmic flexibility, and resource efficiency. To overcome these limitations, we propose ZK-Flex, a flexible and scalable software-hardware co-designed framework for accelerating ZKP proof generation. The software layer incorporates POLY and EC optimizers that reduce computation through hardware- and workload-aware algorithmic choices, while the hardware integrates TCore, a Toom-Cook-based multi-precision core with a flexible NoC and a linked-list memory mechanism that improves parallelism under limited memory capacity. Across representative ZKP benchmarks, ZK-Flex achieves 5 to 11 times speedup and up to 3.8 times higher area efficiency over the state of the art, establishing a new foundation for high-performance, reconfigurable ZKP acceleration.

Problem

• Zero-Knowledge Proofs
• Hardware Acceleration
• Multi-precision Arithmetic
• Workload Utilization
• Reconfigurable Computing

Innovation

• Zero-Knowledge Proofs
• Hardware Acceleration
• Multi-precision Arithmetic
• Software-Hardware Co-design
• Toom-Cook Algorithm