Optimizing the number of multigrid cycles in the full multigrid algorithm

Thekale A, Gradl T, Klamroth K, Rüde U (2010)

Publication Type: Journal article

Publication year: 2010

Journal

Numerical Linear Algebra With Applications Wiley-Blackwell

Book Volume: 17

Pages Range: 199-210

Journal Issue: 2-3

DOI: 10.1002/nla.697

Abstract

Multigrid (MG) methods are among the most efficient and widespread methods for solving large linear systems of equations that arise, for example, from the discretization of partial differential equations. In this paper we introduce a new approach for optimizing the computational cost of the full MG method to achieve a given accuracy by determining the number of MG cycles on each level. To achieve this, a very efficient and flexible Branch and Bound algorithm is developed. The implementation in the parallel finite element solver Hierarchical Hybrid Grids leads to a significant reduction in CPU time.

Authors with CRIS profile

Tobias Gradl Lehrstuhl für Informatik 10 (Systemsimulation) (LSS) Ulrich Rüde Lehrstuhl für Informatik 10 (Systemsimulation) (LSS)

Additional Organisation(s)

Exzellenz-Cluster Engineering of Advanced Materials (EAM)

Involved external institutions

Bergische Universität Wuppertal DE Germany (DE)

How to cite

APA:

Thekale, A., Gradl, T., Klamroth, K., & Rüde, U. (2010). Optimizing the number of multigrid cycles in the full multigrid algorithm. Numerical Linear Algebra With Applications, 17(2-3), 199-210. https://doi.org/10.1002/nla.697

MLA:

Thekale, A., et al. "Optimizing the number of multigrid cycles in the full multigrid algorithm." Numerical Linear Algebra With Applications 17.2-3 (2010): 199-210.

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