GPU-accelerated Bernstein-Bezier discontinuous Galerkin methods for wave problems
Department of Mathematics, Virginia Tech, 225 Stanger Street, Blacksburg
arXiv:1512.06025 [math.NA], (18 Dec 2015)
@article{chan2015gpuaccelerated,
title={GPU-accelerated Bernstein-Bezier discontinuous Galerkin methods for wave problems},
author={Chan, Jesse and Warburton, T.},
year={2015},
month={dec},
archivePrefix={"arXiv"},
primaryClass={math.NA}
}
We evaluate the computational performance of the Bernstein-Bezier basis for discontinuous Galerkin (DG) discretizations and show how to exploit properties of derivative and lift operators specific to Bernstein polynomials. Issues of efficiency and numerical stability are discussed in the context of a model wave propagation problem. We compare the performance of Bernstein-Bezier kernels to both a straightforward and a block-partitioned implementation of nodal DG kernels in a time-explicit GPU-accelerated DG solver. Computational experiments confirm the advantage of both Bernstein-Bezier and block-partitioned nodal DG kernels over the straightforward implementation at high orders of approximation.
December 22, 2015 by hgpu
