article · Chinese Journal of Aeronautics · 2026

GPGPU-accelerated discontinuous Galerkin method on computational aeroacoustics

Haoyu RU, Peixuan ZOU, Yufei LIU, Chenyu BAO, Xuejun Liu, Hongqiang Lyu

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Abstract

The Discontinuous Galerkin (DG) method combines the strengths of the finite volume and finite element methods, making it ideal for Graphics Processing Unit (GPU) parallel computing. This paper presents a multi-GPU parallel algorithm for the DG method in the simulation of acoustic propagation governed by linearized Euler equations on a three-dimensional unstructured grid, using the Message Passing Interface (MPI) and the Compute Unified Device Architecture (CUDA). Several key memory access optimization strategies are adopted to leverage GPU hardware characteristics, including restructuring data to improve kernel function access efficiency to global memory and utilizing GPU high-speed memory to reduce global memory accesses. To ensure the accuracy and efficiency of parallel computing, a store-then-add strategy is adopted to effectively avoid memory access conflicts, and kernel functions are split to prevent warp divergence. Roofline model tests demonstrate that the performance of the kernel functions is close to the theoretical upper limit. For single-GPU parallel computing, the solver’s accuracy and high performance are validated using a Gaussian pulse example. This achieves approximately 400 times acceleration in the third- and fourth-order accuracy for three-dimensional unstructured grid computations. In multi-GPU parallel computing, MPI and CUDA streams overlap computation and communication. Experimental results show that the strong scalability parallel efficiency of 8 A800 GPUs reaches 81.32%, and the weak scalability parallel efficiency reaches 98.20%. These results demonstrate the excellent performance and scalability of the multi-GPU parallel algorithm implemented for large-scale parallel computing.

Cite this paper

APA 7

RU, H., ZOU, P., LIU, Y., BAO, C., Liu, X., & Lyu, H. (2026). GPGPU-accelerated discontinuous Galerkin method on computational aeroacoustics. Chinese Journal of Aeronautics, 104101. https://doi.org/10.1016/j.cja.2026.104101

MLA 9

RU, Haoyu, et al. “GPGPU-accelerated discontinuous Galerkin method on computational aeroacoustics.” Chinese Journal of Aeronautics, 2026, p. 104101, https://doi.org/10.1016/j.cja.2026.104101.

Chicago

RU, Haoyu, Peixuan ZOU, Yufei LIU, Chenyu BAO, Xuejun Liu, and Hongqiang Lyu. 2026. “GPGPU-accelerated discontinuous Galerkin method on computational aeroacoustics.” Chinese Journal of Aeronautics: 104101. https://doi.org/10.1016/j.cja.2026.104101.

Harvard

RU, H. et al. (2026) ‘GPGPU-accelerated discontinuous Galerkin method on computational aeroacoustics’, Chinese Journal of Aeronautics, p. 104101. Available at: https://doi.org/10.1016/j.cja.2026.104101.

BibTeX

@article{ru2026gpgpu,
  title = {{GPGPU-accelerated discontinuous Galerkin method on computational aeroacoustics}},
  author = {RU, Haoyu and ZOU, Peixuan and LIU, Yufei and BAO, Chenyu and Liu, Xuejun and Lyu, Hongqiang},
  journal = {Chinese Journal of Aeronautics},
  pages = {104101},
  year = {2026},
  doi = {10.1016/j.cja.2026.104101}
}

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