Preconditioned Eigensolvers

by Andrew Knyazev

What is "preconditioned eigensolvers?" In one sentence those are matrix-free iterative methods for partial eigenvalue problems that take advantage of using preconditioners to accelerate convergence. A complete answer can be found in the papers "Preconditioned eigensolvers - an oxymoron?" and Preconditioned eigensolvers by Andrew Knyazev. See also an article Andrew Knyazev, Volker Mehrmann, and Klaus Neymeyr, Preconditioning in Eigenvalue Computations, SIAM News, v. 35, no. 10, p. 9, December 2003. about Miniworkshop: Preconditioning in Eigenvalue Computations, 03.03. - 09.03.2002, Oberwolfach.

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Specialized Software: Nonoverlap Domain Decomposition Preconditioning

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Parts of this material are based upon work supported by the National Science Foundation under Grants DMS 9501507, DMS 0208773, and DMS 0612751. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.