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arXiv · 1211.0582

High-Order Discontinuous Galerkin Methods by GPU Metaprogramming

Andreas Klöckner·Timothy Warburton·Jan S. Hesthaven
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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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Andreas Klöckner, Timothy Warburton, Jan S. Hesthaven. 2012-11-02. High-Order Discontinuous Galerkin Methods by GPU Metaprogramming. https://arxiv.org/abs/1211.0582

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