The authors have proposed a new Krylov subspace iteration, the quasi-minimal residual algorithm (QMR), for solving non-Hermitian linear systems. In the original implementation of the QMR method, the Lanczos process with look-ahead is used to generate basis vectors for the underlying Krylov subspaces. In the Lanczos algorithm, these basis vectors are computed by means of three-term recurrences. It has been observed that, in finite precision arithmetic, vector iterations based on three-term recursions are usually less robust than mathematically equivalent coupled two-term vector recurrences. This paper presents a look-ahead algorithm that constructs the Lanczos basis vectors by means of coupled two-term recursions. Implementation details are ...
In this report a parallel implementation of the QMR algorithm with look-ahead for solving large spar...
AbstractThe IDR(s) method proposed by Sonneveld and van Gijzen is an effective method for solving no...
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradi...
. Recently, the authors have proposed a new Krylov subspace iteration, the quasi-minimal residual al...
For the solution of linear systems of equations with unsymmetric coefficient matrix, Freund and Nach...
this paper, we have presented an implementation of the look-ahead Lanczos algorithm for non-Hermitia...
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradi...
It is shown how the look-ahead Lanczos process (combined with a quasi-minimal residual QMR) approach...
Many applications require the solution of multiple linear systems that have the same coefficient mat...
AbstractMany applications require the solution of multiple linear systems that have the same coeffic...
For the solution of large sparse systems of linear equations with general non-Hermitian coefficient ...
A new version of the unsymmetric Lanczos algorithm without look-ahead is described combining element...
A new version of the unsymmetric Lanczos algorithm without look-ahead is described combining element...
Among the iterative methods for solving large linear systems with a sparse (or, possibly, structured...
In the present paper, we introduce a new extension of the conjugate residual (CR) for solving non-He...
In this report a parallel implementation of the QMR algorithm with look-ahead for solving large spar...
AbstractThe IDR(s) method proposed by Sonneveld and van Gijzen is an effective method for solving no...
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradi...
. Recently, the authors have proposed a new Krylov subspace iteration, the quasi-minimal residual al...
For the solution of linear systems of equations with unsymmetric coefficient matrix, Freund and Nach...
this paper, we have presented an implementation of the look-ahead Lanczos algorithm for non-Hermitia...
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradi...
It is shown how the look-ahead Lanczos process (combined with a quasi-minimal residual QMR) approach...
Many applications require the solution of multiple linear systems that have the same coefficient mat...
AbstractMany applications require the solution of multiple linear systems that have the same coeffic...
For the solution of large sparse systems of linear equations with general non-Hermitian coefficient ...
A new version of the unsymmetric Lanczos algorithm without look-ahead is described combining element...
A new version of the unsymmetric Lanczos algorithm without look-ahead is described combining element...
Among the iterative methods for solving large linear systems with a sparse (or, possibly, structured...
In the present paper, we introduce a new extension of the conjugate residual (CR) for solving non-He...
In this report a parallel implementation of the QMR algorithm with look-ahead for solving large spar...
AbstractThe IDR(s) method proposed by Sonneveld and van Gijzen is an effective method for solving no...
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradi...