A Multigrid Method for Adaptive Sparse Grids
Author(s)
Peherstorfer, Benjamin; Zimmer, Stefan; Zenger, Christoph; Bungartz, Hans-Joachim
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Sparse grids have become an important tool to reduce the number of degrees of freedom of discretizations of moderately high-dimensional partial differential equations; however, the reduction in degrees of freedom comes at the cost of an almost dense and unconventionally structured system of linear equations. To guarantee overall efficiency of the sparse grid approach, special linear solvers are required. We present a multigrid method that exploits the sparse grid structure to achieve an optimal runtime that scales linearly with the number of sparse grid points. Our approach is based on a novel decomposition of the right-hand sides of the coarse grid equations that leads to a reformulation in so-called auxiliary coefficients. With these auxiliary coefficients, the right-hand sides can be represented in a nodal point basis on low-dimensional full grids. Our proposed multigrid method directly operates in this auxiliary coefficient representation, circumventing most of the computationally cumbersome sparse grid structure. Numerical results on nonadaptive and spatially adaptive sparse grids confirm that the runtime of our method scales linearly with the number of sparse grid points and they indicate that the obtained convergence factors are bounded independently of the mesh width.
Date issued
2015-10Department
Massachusetts Institute of Technology. Department of Aeronautics and AstronauticsJournal
SIAM Journal on Scientific Computing
Publisher
Society for Industrial and Applied Mathematics
Citation
Peherstorfer, Benjamin, Stefan Zimmer, Christoph Zenger, and Hans-Joachim Bungartz. “A Multigrid Method for Adaptive Sparse Grids.” SIAM Journal on Scientific Computing 37, no. 5 (January 2015): S51–S70. © 2015 Society for Industrial and Applied Mathematics
Version: Final published version
ISSN
1064-8275
1095-7197