GPU Accelerated Discontinuous Galerkin Methods for Shallow Water Equations
Department of Computational and Applied Mathematics, Rice University, 6100 Main Street – MS 134, Houston, TX 77005, USA
arXiv:1403.1661 [math.NA], (7 Mar 2014)
@article{2014arXiv1403.1661G,
author={Gandham}, R and {Medina}, D. and {Warburton}, T},
title={"{GPU Accelerated Discontinuous Galerkin Methods for Shallow Water Equations}"},
journal={ArXiv e-prints},
archivePrefix={"arXiv"},
eprint={1403.1661},
primaryClass={"math.NA"},
keywords={Mathematics – Numerical Analysis},
year={2014},
month={mar},
adsurl={http://adsabs.harvard.edu/abs/2014arXiv1403.1661G},
adsnote={Provided by the SAO/NASA Astrophysics Data System}
}
We discuss the development, verification, and performance of a GPU accelerated discontinuous Galerkin method for the solutions of two dimensional nonlinear shallow water equations. The shallow water equations are hyperbolic partial differential equations and are widely used in the simulation of tsunami wave propagations. Our algorithms are tailored to take advantage of the single instruction multiple data (SIMD) architecture of graphic processing units. The time integration is accelerated by local time stepping based on a multi-rate Adams-Bashforth scheme. A total variational bounded limiter is adopted for nonlinear stability of the numerical scheme. This limiter is coupled with a mass and momentum conserving positivity preserving limiter for the special treatment of a dry or partially wet element in the triangulation. Accuracy, robustness and performance are demonstrated with the aid of test cases. We compare the performance of the kernels expressed in a portable threading language OCCA, when cross compiled with OpenCL, CUDA, and OpenMP at runtime.
March 10, 2014 by hgpu
