ACM Transactions on Mathematical Software (TOMS)
A flexible inner-outer preconditioned GMRES algorithm
SIAM Journal on Scientific Computing
A Restarted GMRES Method Augmented with Eigenvectors
SIAM Journal on Matrix Analysis and Applications
Restarted GMRES preconditioned by deflation
Journal of Computational and Applied Mathematics
Nested Krylov methods based on GCR
Journal of Computational and Applied Mathematics
Analysis of Projection Methods for Solving Linear Systems with Multiple Right-Hand Sides
SIAM Journal on Scientific Computing
Restarted GMRES for Shifted Linear Systems
SIAM Journal on Scientific Computing
Adaptively Preconditioned GMRES Algorithms
SIAM Journal on Scientific Computing
Galerkin Projection Methods for Solving Multiple Linear Systems
SIAM Journal on Scientific Computing
Analysis of acceleration strategies for restarted minimal residual methods
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. III: linear algebra
GMRES with Deflated Restarting
SIAM Journal on Scientific Computing
Truncation Strategies for Optimal Krylov Subspace Methods
SIAM Journal on Numerical Analysis
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
A Technique for Accelerating the Convergence of Restarted GMRES
SIAM Journal on Matrix Analysis and Applications
Recycling Subspace Information for Diffuse Optical Tomography
SIAM Journal on Scientific Computing
The iterative solution of a sequence of linear systems arising from nonlinear finite element analysis
Recycling Krylov Subspaces for Sequences of Linear Systems
SIAM Journal on Scientific Computing
Incremental spectral preconditioners for sequences of linear systems
Applied Numerical Mathematics
Improving the Accuracy of GMRes with Deflated Restarting
SIAM Journal on Scientific Computing
Flexible GMRES with Deflated Restarting
SIAM Journal on Scientific Computing
| Hi-index | 7.29 |
By recycling some error approximations generated during a previous cycle of iterations, we present a technique for improving the convergence of GCRO-DR. The scheme is able to mitigate the occurrence of small skip angles occurring in GCRO-DR, and thus considerably accelerates the convergence. The alternative phenomenon of the residual vectors is examined numerically, and the effectiveness of the new method is illustrated by several examples from practical applications.