A Massively Parallel Multigrid Method with Level Dependent Smoothers for Problems with High Anisotropies

Sebastian Reiter (), Andreas Vogel (), Arne Nägel () and Gabriel Wittum ()
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Sebastian Reiter: Goethe-Universität Frankfurt, G-CSC
Andreas Vogel: Goethe-Universität Frankfurt, G-CSC
Arne Nägel: Goethe-Universität Frankfurt, G-CSC
Gabriel Wittum: Goethe-Universität Frankfurt, G-CSC

A chapter in High Performance Computing in Science and Engineering ´16, 2016, pp 667-675 from Springer

Abstract: Abstract Anisotropic layers, as often seen in biological and geological domains, impose difficulties to several aspects of numerical simulations. In this article we examine how the highly scalable approach to massively parallel geometric multigrid solvers presented in Reiter et al. (Comput Vis Sci 16(4):151–164, 2013) can be extended to problem domains featuring such anisotropies. Considering the real world problem of drug diffusion through the human skin we combine hierarchically distributed multigrids, anisotropic refinement, and level dependent smoothing strategies to create a robust and highly scalable multigrid solver for anisotropic domains.

Keywords: Multigrid; Parallelization; Anisotropy; Smoothing (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-47066-5_45

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DOI: 10.1007/978-3-319-47066-5_45

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