A GPU-Accelerated Hybridizable Discontinuous Galerkin Method for Linear Elasticity

Year:    2020

Author:    Maurice S. Fabien

Communications in Computational Physics, Vol. 27 (2020), Iss. 2 : pp. 513–545

Abstract

We design and analyze an efficient GPU-accelerated hybridizable discontinuous Galerkin method for linear elasticity. Performance analysis of the method is done using the state-of-the-art Time-Accuracy-Size (TAS) spectrum. TAS is a new performance measure which takes into account the accuracy of the solution. Standard performance measures, like floating point operations or run-time, are not completely appropriate for gauging the performance of approximations of continuum mechanics problems, as they neglect the solutions accuracy. A standard roofline model demonstrates that our method is utilizing computational resources efficiently, and as such, significant speed ups over a serial implementation are obtained. By combining traditional performance measures and the novel time-accuracy measures [7] into our performance model, we are able to draw more complete conclusions about which discretizations are best suited for an application. Several numerical experiments validate and verify our numerical scheme.

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.OA-2018-0235

Communications in Computational Physics, Vol. 27 (2020), Iss. 2 : pp. 513–545

Published online:    2020-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    33

Keywords:    GPU-acceleration discontinuous Galerkin hybridization multigrid performance analysis.

Author Details

Maurice S. Fabien

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