Paper 2022/868 Original: eprint.iacr.org/2022/868 ↗
Maximizing the Potential of Custom RISC-V Vector Extensions for Speeding up SHA-3 Hash Functions
Abstract
SHA-3 is considered to be one of the most secure standardized hash functions. It relies on the Keccak-f[1 600] permutation, which operates on an internal state of 1 600 bits, mostly represented as a 5×5×64-bit matrix. While software implementations process the state sequentially in chunks of typically 32 or 64 bits, the Keccak-f[1 600] permutation can benefit a lot from speedup through parallelization. This paper is the first to explore the full potential of parallelization of Keccak-f[1 600] in RISC-V based processors through custom vector extensions on 32-bit and 64-bit architectures. %Such a structure is suitable to work under vector instructions in data-parallel operation mode. This paper uses the RISC-V vector extensions to explore its performance in 64-bit and 32-bit architectures. We analyze the Keccak-f[1 600] permutation, composed of five different step mappings, and propose ten custom vector instructions to speed up the computation. We realize these extensions in a SIMD processor described in SystemVerilog. We compare the performance of our hardware/software co-design to a software-only implementation on the one hand and to existing architectures based on (vectorized) hardware/software co-design on the other hand. We show that our design outperforms all related work thanks to our carefully selected custom vector instructions.
Metadata
- Available format(s)
PDF
- Category
- Applications
- Publication info
- Preprint.
- History
- 2022-07-19: last updated
- 2022-07-03: published
- Short URL
- https://ia.cr/2022/868
- License
- https://creativecommons.org/licenses/by/4.0/
BibTeX
@misc{cryptoeprint:2022/868,
author = {Huimin Li and Nele Mentens and Stjepan Picek},
title = {Maximizing the Potential of Custom RISC-V Vector Extensions for Speeding up SHA-3 Hash Functions},
howpublished = {Cryptology {ePrint} Archive, Paper 2022/868},
year = {2022},
url = {https://eprint.iacr.org/2022/868}
}