A technique for accelerating the convergence of restarted GMRES
Journal Article
·
· SIAM Journal on Matrix Analysis and Applications
OSTI ID:15020368
We have observed that the residual vectors at the end of each restart cycle of restarted GMRES often alternate direction in a cyclic fashion, thereby slowing convergence. We present a new technique for accelerating the convergence of restarted GMRES by disrupting this alternating pattern. The new algorithm resembles a full conjugate gradient method with polynomial preconditioning, and its implementation requires minimal changes to the standard restarted GMRES algorithm.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 15020368
- Report Number(s):
- UCRL-JRNL-202883
- Journal Information:
- SIAM Journal on Matrix Analysis and Applications, Journal Name: SIAM Journal on Matrix Analysis and Applications Journal Issue: 4 Vol. 25
- Country of Publication:
- United States
- Language:
- English
Similar Records
Minimal residual method stronger than polynomial preconditioning
Some comparison of restarted GMRES and QMR for linear and nonlinear problems
Toward efficient polynomial preconditioning for GMRES
Conference
·
Sat Dec 31 04:00:00 UTC 1994
·
OSTI ID:223856
Some comparison of restarted GMRES and QMR for linear and nonlinear problems
Conference
·
Sat Dec 31 04:00:00 UTC 1994
·
OSTI ID:219562
Toward efficient polynomial preconditioning for GMRES
Journal Article
·
Thu Dec 30 00:00:00 UTC 2021
· Numerical Linear Algebra with Applications
·
OSTI ID:1838187