A GPU-enabled finite volume solver for large shallow water simulations

TL;DR

This paper develops a GPU-accelerated finite volume solver for large-scale shallow water simulations, demonstrating significant speed improvements over CPU implementations while maintaining accuracy across various problem sizes.

Contribution

It introduces a GPU-based implementation of the HLLC finite volume solver for 2D shallow water problems, highlighting performance gains and practical GPU integration.

Findings

GPU implementation achieves faster computation times than CPU.

Accuracy remains consistent between GPU and CPU solutions.

Speed gains depend on GPU model, problem size, and simulation duration.

Abstract

This paper presents the implementation of a HLLC finite volume solver using GPU technology for the solution of shallow water problems in two dimensions. It compares both CPU and GPU approaches for implementing all the solver's steps. The technology of graphics and central processors is highlighted with a particular emphasis on the CUDA architecture of NVIDIA. The simple and well-documented Application Programming Interface (CUDA API) facilitates the use of the display card workstation as an additional computer unit to the central processor. Four professional solutions of the NVIDIA Quadro line are tested. Comparison tests between CPU and GPU are carried out on unstructured grids of small sizes (up to 10,000 elements), medium and large sizes (up to 10,000,000 elements). For all test cases, the accuracy of results is of the same order of magnitude for both approaches. Furthermore, the obtained speed gains with the GPU strongly depend on the model of the graphics card, the size of the problem and the simulation time.