Paper 2026/012 Original: eprint.iacr.org/2026/012 ↗

HIGH: Harnessing GPU Parallelism for Optimized HQC Performance

Jiankuo Dong
Yuze Hou
Shiqin Wang
Letian Sha
Fu Xiao
Zhenjiang Dong
Jingqiang Lin
Abstract

Hamming Quasi-Cyclic (HQC) was a candidate algorithm in the fourth round of the National Institute of Standards and Technology (NIST) post-quantum cryptography (PQC) standardization process and was ultimately selected as a standardized cryptographic scheme in the latest round. To date, although HQC has been optimized for FPGA, CPU, and other platforms, research on GPU-based parallel acceleration remains significantly underexplored. Given this, our research aims to investigate the feasibility and efficiency of hand-optimized HQC implementations on GPU, addressing the current research gap in GPU-based implementations of code-based cryptographic algorithms. In this paper, we introduce a High-performance Implementation of GPU-based HQC, named HIGH. First, we propose a novel architecture for coding-based PQC implementations, significantly reducing redundant global memory access through core fusion. Second, we design a HIKD structure for HIGH, combining a high-order multiplication scheme (HIK) and a low-order multiplication scheme (HID), achieving an impressive 85.6\% improvement over Official fourth round Optimized Implementation. Third, through extensive experimentation, we sought the optimal HIKD combination and identified the optimal parallel parameters, leveraging these optimizations, HIGH surpasses current state-of-the-art benchmarks, with Key Generation, Encapsulation, and Decapsulation performance increased by 20$\times$, 32$\times$, and 39$\times$, respectively.

Metadata
Available format(s)
PDF
Category
Public-key cryptography
Publication info
Preprint.
History
2026-01-05: last updated
2026-01-05: published
Short URL
https://ia.cr/2026/012
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2026/012,
      author = {Jiankuo Dong and Yuze Hou and Shiqin Wang and Letian Sha and Fu Xiao and Zhenjiang Dong and Jingqiang Lin},
      title = {HIGH: Harnessing GPU Parallelism for Optimized HQC Performance},
      howpublished = {Cryptology {ePrint} Archive, Paper 2026/012},
      year = {2026},
      url = {https://eprint.iacr.org/2026/012}
}
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