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Adaptive Algebraic Multigrid

2006; Society for Industrial and Applied Mathematics; Volume: 27; Issue: 4 Linguagem: Inglês

10.1137/040614402

1095-7197

Marian Brezina, Robert D. Falgout, Scott MacLachlan, Thomas A. Manteuffel, Stephen F. McCormick, J. Ruge,

Matrix Theory and Algorithms

Efficient numerical simulation of physical processes is constrained by our ability to solve the resulting linear systems, prompting substantial research into the development of multiscale iterative methods capable of solving these linear systems with an optimal amount of effort. Overcoming the limitations of geometric multigrid methods to simple geometries and differential equations, algebraic multigrid methods construct the multigrid hierarchy based only on the given matrix. While this allows for efficient black‐box solution of the linear systems associated with discretizations of many elliptic differential equations, it also results in a lack of robustness due to unsatisfied assumptions made on the near null spaces of these matrices. This paper introduces an extension to algebraic multigrid methods that removes the need to make such assumptions by utilizing an adaptive process. Emphasis is on the principles that guide the adaptivity and their application to algebraic multigrid solution of certain symmetric positive‐definite linear systems.