z-logo
open-access-imgOpen Access
Iterative methods for solvingAx=b, GMRES/FOM versus QMR/BiCG
Author(s) -
Jane Cullum
Publication year - 1996
Publication title -
advances in computational mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.003
H-Index - 61
eISSN - 1572-9044
pISSN - 1019-7168
DOI - 10.1007/bf02127693
Subject(s) - generalized minimal residual method , mathematics , residual , eigenvalues and eigenvectors , convergence (economics) , matrix (chemical analysis) , norm (philosophy) , outlier , algorithm , statistics , physics , materials science , quantum mechanics , political science , law , economics , composite material , economic growth
We study the convergence of the GMRES/FOM and QMR/BiCG methods for solving nonsymmetric systems of equations=. We prove, in exact arithmetic, that any type of residual norm convergence obtained using BiCG can also be obtained using FOM but on a different system of equations. We consider practical comparisons of these procedures when they are applied to the same matrices. We use a unitary invariance shared by both methods, to construct test matrices where we can vary the nonnormality of the test matrix by variations in simplified eigenvector matrices. We used these test problems in two sets of numerical experiments. The first set of experiments was designed to study effects of increasing nonnormality on the convergence of GMRES and QMR. The second set of experiments was designed to track effects of the eigenvalue distribution on the convergence of QMR. In these tests the GMRES residual norms decreased significantly more rapidly than the QMR residual norms but without corresponding decreases in the error norms. Furthermore, as the nonnormality of was increased, the GMRES residual norms decreased more rapidly. This led to premature termination of the GMRES procedure on highly nonnormal problems. On the nonnormal test problems the QMR residual norms exhibited less sensitivity to changes in the nonnormality. The convergence of either type of procedure, as measured by the error norms, was delayed by the presence of large or small outliers and affected by the type of eigenvalues, real or complex, in the eigenvalue distribution of. For GMRES this effect can be seen only in the error norm plots.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom