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2013 | OriginalPaper | Buchkapitel

23. High-Order Discontinuous Galerkin Methods by GPU Metaprogramming

verfasst von : Andreas Klöckner, Timothy Warburton, Jan S. Hesthaven

Erschienen in: GPU Solutions to Multi-scale Problems in Science and Engineering

Verlag: Springer Berlin Heidelberg

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Abstract

Discontinuous Galerkin (DG) methods for the numerical solution of partial differential equations have enjoyed considerable success because they are both flexible and robust: They allow arbitrary unstructured geometries and easy control of accuracy without compromising simulation stability. In a recent publication, we have shown that DG methods also adapt readily to execution on modern, massively parallel graphics processors (GPUs). A number of qualities of the method contribute to this suitability, reaching from locality of reference, through regularity of access patterns, to high arithmetic intensity. In this article, we illuminate a few of the more practical aspects of bringing DG onto a GPU, including the use of a Python-based metaprogramming infrastructure that was created specifically to support DG, but has found many uses across all disciplines of computational science.

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Titel: High-Order Discontinuous Galerkin Methods by GPU Metaprogramming
verfasst von: Andreas Klöckner
Timothy Warburton
Jan S. Hesthaven
Verlag: Springer Berlin Heidelberg
Buch: GPU Solutions to Multi-scale Problems in Science and Engineering
Print ISBN: 978-3-642-16404-0

Electronic ISBN: 978-3-642-16405-7

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-3-642-16405-7_23

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