Bernstein-Bézier weight-adjusted discontinuous Galerkin methods for wave propagation in heterogeneous media

•A DG scheme for wave propagation in arbitrary heterogeneous media is presented.•Sparse matrix-based implementation of the Bernstein polynomial multiplication.•Representation of the Bernstein polynomial projection matrix in terms of sparse matrices.•Computational complexity is reduced from O(N2d) to...

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Vydáno v:Journal of computational physics Ročník 400; s. 108971
Hlavní autoři: Guo, Kaihang, Chan, Jesse
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cambridge Elsevier Inc 01.01.2020
Elsevier Science Ltd
Témata:
Algorithms
Bernstein
Complexity
Computational physics
Computer simulation
Discontinuous Galerkin
Galerkin method
GPU
Heterogeneous media
High order
Mathematical analysis
Multiplication
Polynomials
Propagation
Wave propagation
Weight
Discontinuous Galerkin
Bernstein
GPU
Heterogeneous media
High order
ISSN:0021-9991, 1090-2716
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Shrnutí:•A DG scheme for wave propagation in arbitrary heterogeneous media is presented.•Sparse matrix-based implementation of the Bernstein polynomial multiplication.•Representation of the Bernstein polynomial projection matrix in terms of sparse matrices.•Computational complexity is reduced from O(N2d) to O(Nd+1) in d dimensions.•GPU implementation achieves significant speedups with respect to quadrature-base ap-proach. This paper presents an efficient discontinuous Galerkin method to simulate wave propagation in heterogeneous media with sub-cell variations. This method is based on a weight-adjusted discontinuous Galerkin method (WADG), which achieves high order accuracy for arbitrary heterogeneous media [1]. However, the computational cost of WADG grows rapidly with the order of approximation. In this work, we propose a Bernstein-Bézier weight-adjusted discontinuous Galerkin method (BBWADG) to address this cost. By approximating sub-cell heterogeneities by a fixed degree polynomial, the main steps of WADG can be expressed as polynomial multiplication and L2 projection, which we carry out using fast Bernstein algorithms. The proposed approach reduces the overall computational complexity from O(N2d) to O(Nd+1) in d dimensions. Numerical experiments illustrate the accuracy of the proposed approach, and computational experiments for a GPU implementation of BBWADG verify that this theoretical complexity is achieved in practice.
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ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2019.108971