🚀 Accelerated libiop by Optimizing Additive FFT Algorithms
This repository is a fork of libiop focusing on optimizing additive Fast Fourier Transform (FFT) algorithms used in the original repository.
This library uses the Cantor additive FFT implemented in the additive-fft library and demonstrates notable performance gains in the current Aurora [BCRSVW] implementation over the Gao–Mateer (GM) algorithm provided in libiop across all input sizes, and over the LCH algorithm re-implemented in additive-fft for smaller circuits, which are prevalent in many zkSNARK applications.
We achieved about ~40% performance improvement on the Aurora while maintaining correctness and interface compatibility with upstream libiop.
WARNING: This is an academic proof-of-concept prototype, and in particular has not received careful code review.
This implementation is NOT ready for production use.
Please follow the installation instructions.
| Prover: GM | Prover: Cantor | Prover: LCH | Verifier: GM | Verifier: Cantor | Verifier: LCH | ||
|---|---|---|---|---|---|---|---|
| 9 | 16 | 0.44 | 0.33 | 0.35 | 0.04 | 0.04 | 0.04 |
| 10 | 17 | 0.90 | 0.67 | 0.71 | 0.05 | 0.05 | 0.05 |
| 11 | 18 | 1.87 | 1.36 | 1.44 | 0.07 | 0.06 | 0.07 |
| 12 | 19 | 3.99 | 2.91 | 2.93 | 0.10 | 0.09 | 0.10 |
| 13 | 20 | 8.53 | 6.02 | 5.95 | 0.17 | 0.15 | 0.16 |
| 14 | 21 | 19.47 | 12.01 | 12.44 | 0.29 | 0.26 | 0.28 |
| 15 | 22 | 41.05 | 25.27 | 25.41 | 0.54 | 0.48 | 0.52 |
| 16 | 23 | 84.26 | 50.83 | 50.63 | 1.02 | 0.93 | 1.00 |
| 17 | 24 | 176.67 | 104.26 | 102.95 | 1.98 | 1.79 | 1.93 |
| 18 | 25 | 373.83 | 216.00 | 213.61 | 3.88 | 3.51 | 3.78 |
| 19 | 26 | 771.42 | 443.88 | 441.51 | 7.78 | 6.91 | 7.44 |
All measurements were taken with Google Benchmark, with a minimum 10-second warm-up period, on:
- CPU: AMD Ryzen 9 9950X @ 5.7 GHz
- RAM: 64 GB DDR5
- OS: Debian 12 with kernel 6.12.12
The codeword length is set to
This library is licensed under the MIT License.
This work was supported by BTQ Technologies Corp. and Mitacs.
If you use this repository or the additive FFT optimizations in your research, please cite our paper:
@InProceedings{10.1007/978-3-032-10536-3_13,
author="Badakhshan, Mohammadtaghi
and Samanta, Susanta
and Gong, Guang",
editor="Boura, Christina
and Mashatan, Atefeh
and Miri, Ali",
title="Accelerating Post-quantum Secure {zkSNARKs} by Optimizing Additive {FFT}",
booktitle="Selected Areas in Cryptography -- SAC 2025",
year="2026",
publisher="Springer Nature Switzerland",
address="Cham",
pages="339--368",
isbn="978-3-032-10536-3"
}