On GPU acceleration of PQC algorithms

Daniel Römer; Gero Knoblauch; Alexander Wiesmaier

Paper 2025/1596

On GPU acceleration of PQC algorithms

Daniel Römer, Hochschule Darmstadt - University of Applied Sciences

Gero Knoblauch, Hochschule Darmstadt - University of Applied Sciences, National Research Center for Applied Cybersecurity ATHENE

Alexander Wiesmaier

, Hochschule Darmstadt - University of Applied Sciences, European University of Technology, European Union, National Research Center for Applied Cybersecurity ATHENE

Abstract

The rise of quantum computers results in many cryptographic systems being no longer considered sufficiently secure. Algorithms from the field of post-quantum cryptography promise to provide security against the new systems. However, PQC algorithms are generally more computationally intensive than classical cryptography. In order to increase suitability of PQC for everyday use, this paper investigates their acceleration using GPUs. For this purpose, we analyzed research in the field and closed some gaps with our own implementations. We implemented Dilithium, FrodoKEM, and SPHINCS+ on GPUs using CUDA and benchmarked them together with an existing GPU implementation of Kyber on a Tesla A100 and on a RTX 2070 Super. Dilithium performed convincingly on both GPUs, achieving speed-ups in key generation, signing, and verify by factors of around 820, 2,724 and 2,609 on the A100 and 198, 714 and 802 on the RTX 2070 using the optimal batch sizes. SPHINCS+ achieved speed-ups by factors of around 715, 4,114 and 5,915 on the A100 and 193, 193 and 134 on the RTX 2070. FrodoKEM’s key generation, encapsulation, and decapsulation on the A100 were accelerated by factors of 9,989, 4,726, and 3,566. It performed speed-up factors of 107, 108, and 206 on the RTX 2070, respectively. We compared to Kyber's acceleration factors of 476, 513 and 1782 on the A100 and 18.5, 17.4 and 184.5 on the RTX 2070. In addition, we investigated the effect of using a variable set of CUDA streams for FrodoKEM. Here, using 8 streams, a speedup of another 2% could be achieved.

Metadata

Available format(s): PDF
Category: Implementation
Publication info: Preprint.
Keywords: PQC GPU acceleration CUDA
Contact author(s): daniel c roemer @ stud h-da de
Gero Knoblauch @ h-da de
alexander wiesmaier @ h-da de
History: 2025-09-11: approved; 2025-09-04: received; See all versions
Short URL: https://ia.cr/2025/1596
License: CC BY

BibTeX

@misc{cryptoeprint:2025/1596,
      author = {Daniel Römer and Gero Knoblauch and Alexander Wiesmaier},
      title = {On {GPU} acceleration of {PQC} algorithms},
      howpublished = {Cryptology {ePrint} Archive, Paper 2025/1596},
      year = {2025},
      url = {https://eprint.iacr.org/2025/1596}
}