GPU-acceleration of the Discontinuous Galerkin Shallow Water Equations Solver (DG-SWEM) using CUDA and OpenACC
Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin
arXiv:2508.21208 [physics.comp-ph], (28 Aug 2025)
@misc{wichitrnithed2025gpuaccelerationdiscontinuousgalerkinshallow,
title={GPU-acceleration of the Discontinuous Galerkin Shallow Water Equations Solver (DG-SWEM) using CUDA and OpenACC},
author={Chayanon Wichitrnithed and Eirik Valseth and Clint Dawson},
year={2025},
eprint={2508.21208},
archivePrefix={arXiv},
primaryClass={physics.comp-ph},
url={https://arxiv.org/abs/2508.21208}
}
This paper presents a porting of DG-SWEM, a discontinuous Galerkin solver for coastal ocean circulation, and in particular storm surge, to GPU using two separate approaches: CUDA Fortran and OpenACC. Time-explicit discontinuous Galerkin methods have been shown to exhibit a large amount of data parallelism due to the loose coupling between elements, and thus are naturally mapped to the GPU architecture. For each porting approach, we discuss the code design, ease of programming, and performance when running on realistic use cases. Specifically for the OpenACC version, we also aim to preserve maintainability within the same codebase through using Unified Memory. We test the codes on NVIDIA’s Grace Hopper chip and compare the GPU performance on each node to the MPI version on a single CPU node (144 cores).
September 7, 2025 by hgpu
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