Need for zkSpeed: Accelerating HyperPlonk for Zero-Knowledge Proofs
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz, Ramesh Karri, Siddharth Garg, Brandon Reagen
Abstract
Zero-Knowledge Proofs (ZKPs) are a rapidly growing technique for privacy-preserving and verifiable computation.ZKPs enable one party (a prover: P) to prove to another (a verifier: V) that a statement is true or correct without revealing any additional information.This powerful capability has led to ZKPs being applied and proposed for application in blockchain technologies, verifiable machine learning, and electronic voting.However, ZKPs have yet to see widespread, ubiquitous adoption due to the exceptionally high computational complexity of the proving process.Naturally, there has been recent work to accelerate ZKP primitives and protocols using GPUs and ASICs.However, the protocols considered so far face one of two challenges: they require a trusted setup for each new application or generate large proofs with high verification costs, limiting their applicability in scenarios with numerous verifiers or strict verification time constraints.HyperPlonk is a state-of-theart ZKP protocol that supports both one-time, universal setup and small proof sizes/verification costs expected by publicly verifiable, consensus-based systems (e.g., blockchain).While HyperPlonk's setup and verifier properties are highly desirable, the proving phase is costly.A HyperPlonk prover must compute on large bitwidths (e.g., 255-381b) and polynomials (e.g., of degree 2 24 ), employs computationally (e.g., MSM) and bandwidth (e.g., SumCheck) intensive kernels, and the complete protocol comprises many steps, each constituting distinct kernels.We present an accelerator, zkSpeed, to
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext b6cb6ddb-11ea-494e-8045-45c4bc0d8020Cited by top-tier papers5
- zkPHIRE: A Programmable Accelerator for ZKPs over HIgh-degRee, Expressive GatesAlhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz et al.HPCA 2026 · 1 citation
- Transparent Dictionaries from Polynomial CommitmentsHossein Hafezi, Alireza Shirzad, Benedikt Bünz, Joseph BonneauUSENIX Security 2026 · 1 citation
- Zero-Knowledge AI Inference with High PrecisionArman Riasi, Haodi Wang, Rouzbeh Behnia, Viet Vo et al.CCS 2025
- TensorZKP: Repurposing GPU Tensor Cores for High-Performance Zero-Knowledge ProofsTao Lu, Jipeng Zhang, Yanpei Guo, Xuanming Liu et al.USENIX Security 2026
- GenZA: A General and Efficient Accelerator for Diverse Zero-Knowledge Proof ProtocolsCheng Wang, Jiangbin Dong, Mingyu GaoISCA 2026
Builds on27
- F1: A Fast and Programmable Accelerator for Fully Homomorphic EncryptionNikola Samardzic, Axel Feldmann, Aleksandar Krastev, Srinivas Devadas et al.MICRO 2021 · 294 citations
- Spartan: Efficient and General-Purpose zkSNARKs Without Trusted SetupSrinath T. V. SettyCRYPTO 2020 · 262 citations
- CraterLake: a hardware accelerator for efficient unbounded computation on encrypted dataNikola Samardzic, Axel Feldmann, Aleksandar Krastev, Nathan Manohar et al.ISCA 2022 · 205 citations
- BTS: an accelerator for bootstrappable fully homomorphic encryptionSangpyo Kim, Jongmin Kim, Michael Jaemin Kim, Wonkyung Jung et al.ISCA 2022 · 184 citations
- ARK: Fully Homomorphic Encryption Accelerator with Runtime Data Generation and Inter-Operation Key ReuseJongmin Kim, Gwangho Lee, Sangpyo Kim, Gina Sohn et al.MICRO 2022 · 160 citations
Related papers
- Pipelonk: Accelerating End-to-End Zero-Knowledge Proof Generation on GPUs for PLONK-Based ProtocolsZhiyuan Zhang, Yanxin Cai, Wenhao Yin, Xueyu Wu et al.PPoPP 2026 · 1 citation
- BatchZK: A Fully Pipelined GPU-Accelerated System for Batch Generation of Zero-Knowledge ProofsTao Lu, Yuxun Chen, Zonghui Wang, Xiaohang Wang et al.ASPLOS 2025 · 11 citations
- UniZK: Accelerating Zero-Knowledge Proof with Unified Hardware and Flexible Kernel MappingCheng Wang, Mingyu GaoASPLOS 2025 · 12 citations
- PipeZK: Accelerating Zero-Knowledge Proof with a Pipelined ArchitectureYe Zhang, Shuo Wang, Xian Zhang, Jiangbin Dong et al.ISCA 2021 · 87 citations
- Accelerating Zero-Knowledge Proofs Through Hardware-Algorithm Co-DesignNikola Samardzic, Simon Langowski, Srinivas Devadas, Daniel SánchezMICRO 2024 · 24 citations
