Pipelonk: Accelerating End-to-End Zero-Knowledge Proof Generation on GPUs for PLONK-Based Protocols
Zhiyuan Zhang, Yanxin Cai, Wenhao Yin, Xueyu Wu, Yi Wang, Lei Ju, Zhuoran Ji
Abstract
Zero-knowledge proofs (ZKPs) are cryptographic protocols that allow verification of statements without disclosing the underlying information. Among them, PLONK-based ZKPs are particularly notable for offering succinct, non-interactive proofs of knowledge with a universal trusted setup, leading to widespread adoption in blockchain and cryptocurrency applications. Nonetheless, their broader deployment is hindered by long proof-generation times and substantial memory demands. While GPUs can accelerate these computations, their limited memory capacity introduces significant challenges for efficient end-to-end proof generation.
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