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Projection acceleration of Krylov solvers
Author(s) -
Vuik C.,
Tang J.M.,
Nabben R.
Publication year - 2007
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200700949
Subject(s) - convergence (economics) , eigenvalues and eigenvectors , projection (relational algebra) , acceleration , mathematics , projection method , computer science , mathematical optimization , algorithm , dykstra's projection algorithm , physics , classical mechanics , quantum mechanics , economics , economic growth
In many applications it appears that the initial convergence of preconditioned Krylov solvers is slow. The reason for this is that a number of small eigenvalues are present. After these bad eigenvector components are approximated, the fast superlinear convergence sets in. A way to have fast convergence from the start is to remove these components by a projection. In this paper we give a comparison of some of these projection operators. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)