Paper 2026/012

HIGH: Harnessing GPU Parallelism for Optimized HQC Performance

Jiankuo Dong, Nanjing University of Posts and Telecommunications
Yuze Hou, Nanjing University of Posts and Telecommunications
Shiqin Wang, Nanjing University of Posts and Telecommunications
Letian Sha, Nanjing University of Posts and Telecommunications
Fu Xiao, Nanjing University of Posts and Telecommunications
Zhenjiang Dong, Nanjing University of Posts and Telecommunications
Jingqiang Lin, University of Science and Technology of China
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.
Keywords
PQCHQCKaratsubaPolynomial MultiplicationGPU
Contact author(s)
djiankuo @ foxmail com
1223045638 @ njupt edu cn
1023040807 @ njupt edu cn
History
2026-01-09: approved
2026-01-05: received
See all versions
Short URL
https://ia.cr/2026/012
License
Creative Commons Attribution
CC BY

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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