Saturday, November 1

MS17
Lanczos-Type Methods

10:00 AM-12:00 PM
Room: Ballroom 2

Among the iterative methods for solving large linear systems or eigenvalue problems with a sparse nonsymmetric matrix, those that are based on the Lanczos process feature low computational cost and low memory requirements.In the last ten years much progress has been made regarding new, faster converging algorithms, avoiding breakdowns by look-ahead, understanding other stability problems, and taking appropriate measure to avoid or reduce them. New related results for the symmetric case are also of high relevance. In this minisymposium, the speakers will present some of the most recent findings. The presentations should be of interest to a wide audience of people applying or investigating iterative methods.

Organizer: Martin H. Gutknecht
ETH-Zentrum, Switzerland

These abstracts are posted as PostScript files at http://www.scsc.ethz.ch/~mhg/SIAM-ALAabstr.ps

10:00 On the Role of the Left Starting Vector in the Nonsymmetric Lanczos Algorithm

Anne Greenbaum, Courant Institute of Mathematical Sciences, New York University

10:30 Look-Ahead Lanczos Revisited

Martin H. Gutknecht, Organizer; and Marlis Hochbruck, Universitat Tubingen, Germany

11:00 The Main Effects of Rounding Errors in Krylov Solvers for Symmetric Linear Systems

Gerard Sleijpen and Henk van der Vorst, University of Utrecht, The Netherlands; and Jan Modersitzki, Medical University of Lubeck, Germany

11:30 Residual Smoothing: Does it Help at All?

Martin H. Gutknecht, Organizer

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