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On some versions of the element agglomeration AMGe method
Authors:Ilya Lashuk  Panayot S Vassilevski
Institution:1. Department of Mathematical Sciences, University of Colorado at Denver, Denver, CO 80217, U.S.A.;2. Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, 7000 East Avenue, Mail‐Stop L‐560, Livermore, CA 94551, U.S.A.
Abstract:The present paper deals with element‐based algebraic multigrid (AMGe) methods that target linear systems of equations coming from finite element discretizations of elliptic partial differential equations. The individual element information (element matrices and element topology) is the main input to construct the AMG hierarchy. We study a number of variants of the spectral agglomerate AMGe method. The core of the algorithms relies on element agglomeration utilizing the element topology (built recursively from fine to coarse levels). The actual selection of the coarse degrees of freedom is based on solving a large number of local eigenvalue problems. Additionally, we investigate strategies for adaptive AMG as well as multigrid cycles that are more expensive than the V‐cycle utilizing simple interpolation matrices and nested conjugate gradient (CG)‐based recursive calls between the levels. The presented algorithms are illustrated with an extensive set of experiments based on a matlab implementation of the methods. Copyright © 2008 John Wiley & Sons, Ltd.
Keywords:algebraic multigrid  element agglomeration  adaptive AMG  nested‐CG cycle MG
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