Work

FluxZK: Scalable and Efficient Zero-Knowledge Proof Computation via GPU Acceleration — SC26 Artifact

Year: 2026

Type: software

Abstract: This record contains the frozen artifact accompanying the SC26 paper “FluxZK: Scalable and Efficient Zero-Knowledge Proof Computation via GPU Acceleration.” FluxZK is a CUDA-based library for accelerating zero-knowledge proof computations on GPUs. The artifact includes implementations and artifact-evaluation workflows for GPU Montgomery arithmetic, multi-scalar multiplication (MSM), in-GPU number-theoretic transform (NTT), and out-of-core NTT.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22089198

Authors: Qiang, Xinwei, Yu, Liukun, Wang, Xiyu, Li, Zhengyi, Sun, Shixuan, Leng, Jingwen, Chen, Chen, Gui, Jiaping, Zheng, Zhenzhe, Dong, Jin, Guo, Minyi

Institution: Shanghai Jiao Tong University

Language: English

Topic: Cryptography and Residue Arithmetic

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7204203959

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