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On the performance of various adaptive preconditioned GMRES strategies

✍ Scribed by Kevin Burrage; Jocelyne Erhel

Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
172 KB
Volume
5
Category
Article
ISSN
1070-5325

No coin nor oath required. For personal study only.

✦ Synopsis

This paper compares the performance on linear systems of equations of three similar adaptive accelerating strategies for restarted GMRES. The underlying idea is to adaptively use spectral information gathered from the Arnoldi process. The first strategy retains approximations to some eigenvectors from the previous restart and adds them to the Krylov subspace. The second strategy also uses approximated eigenvectors to define a preconditioner at each restart. This paper designs a third new strategy which combines elements of both previous approaches. Numerical results show that this new method is both more efficient and more robust.

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