Welcome to the resource topic for 2023/1503
Title:
zk-Bench: A Toolset for Comparative Evaluation and Performance Benchmarking of SNARKs
Authors: Jens Ernstberger, Stefanos Chaliasos, George Kadianakis, Sebastian Steinhorst, Philipp Jovanovic, Arthur Gervais, Benjamin Livshits, Michele Orrù
Abstract:Zero-Knowledge Proofs (ZKPs), especially Succinct Non-interactive ARguments of Knowledge (SNARKs), have garnered significant attention in modern cryptographic applications. Given the multitude of emerging tools and libraries, assessing their strengths and weaknesses is nuanced and time-consuming. Often, claimed results
are generated in isolation, and omissions in details render them irreproducible. The lack of comprehensive benchmarks, guidelines, and support frameworks to navigate the ZKP landscape effectively is a major barrier in the development of ZKP applications.
In response to this need, we introduce zk-Bench, the first benchmarking framework and estimator tool designed for performance evaluation of public-key cryptography, with a specific focus on practical assessment of general-purpose ZKP systems. To simplify navigating the complex set of metrics and qualitative properties, we offer a comprehensive open-source evaluation platform, which enables the rigorous dissection and analysis of tools for ZKP development to uncover their trade-offs throughout the entire development stack; from low-level arithmetic libraries, to high-level tools for SNARK development.
Using zk-Bench, we (i) collect data across 13 different elliptic curves implemented across 9 libraries, (ii) evaluate 5 tools for ZKP development and (iii) provide a tool for estimating cryptographic protocols, instantiated for the \mathcal{P}\mathfrak{lon}\mathcal{K} proof system, achieving an accuracy of 6 − 32% for ZKP circuits with up to millions of gates. By evaluating zk-Bench for various hardware configurations, we find that certain tools for ZKP development favor compute-optimized hardware, while others benefit from memory-optimized hardware. We observed performance enhancements of up to 40 % for memory-optimized configurations and 50 % for compute-optimized configurations, contingent on the specific ZKP development tool utilized.
ePrint: https://eprint.iacr.org/2023/1503
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