Add to ORKGWe discuss the design and implementation of a suite of functions for solving symmetric indefinite linear systems associated with mixed approximation of systems of PDEs. The novel feature of our iterative solver is the incorporation of error control in the natural "energy" norm in combination with an a posteriori estimator for the PDE approximation error. This leads to a robust and optimally efficient stopping criterion: the iteration is terminated as soon as the algebraic error is insignificant compared to the approximation error. We describe a "proof of concept" MATLAB implementation of this algorithm and we illustrate its effectiveness when integrated into the Incompressible Flow Iterative Solution Software (IFISS) package (cf. A...
We propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of e...
Iterative methods for the solution of linear systems of equations produce a sequence of approximate ...
Abstract. The three-term Lanczos process for a symmetric matrix leads to bases for Krylov subspaces ...
We discuss the design and implementation of a suite of functions for solving symmetric indefinite li...
We discuss the design and implementation of a suite of functions for solving symmetric indefi-nite l...
We discuss the design and implementation of a suite of functions for solving symmetric indefinite l...
This work discusses the design of efficient algorithms for solving symmetric indefinite linear syste...
The central theme of this thesis is the design of optimal balanced black-box stopping criteria in it...
This paper discusses the design and implementation of efficient solution algorithms for symmetric li...
The threeterm Lanczos process for a symmetric matrix leads to bases for Krylov subspaces of incre...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
For iterative solution of symmetric systems the conjugate gradient method (CG) is commonly used whe...
Abstract. CG, SYMMLQ, and MINRES are Krylov subspace methods for solving symmetric systems of linear...
10.1007/s10589-006-9006-8Computational Optimization and Applications362-3221-247CPPP
We propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of e...
We propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of e...
Iterative methods for the solution of linear systems of equations produce a sequence of approximate ...
Abstract. The three-term Lanczos process for a symmetric matrix leads to bases for Krylov subspaces ...
We discuss the design and implementation of a suite of functions for solving symmetric indefinite li...
We discuss the design and implementation of a suite of functions for solving symmetric indefi-nite l...
We discuss the design and implementation of a suite of functions for solving symmetric indefinite l...
This work discusses the design of efficient algorithms for solving symmetric indefinite linear syste...
The central theme of this thesis is the design of optimal balanced black-box stopping criteria in it...
This paper discusses the design and implementation of efficient solution algorithms for symmetric li...
The threeterm Lanczos process for a symmetric matrix leads to bases for Krylov subspaces of incre...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
For iterative solution of symmetric systems the conjugate gradient method (CG) is commonly used whe...
Abstract. CG, SYMMLQ, and MINRES are Krylov subspace methods for solving symmetric systems of linear...
10.1007/s10589-006-9006-8Computational Optimization and Applications362-3221-247CPPP
We propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of e...
We propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of e...
Iterative methods for the solution of linear systems of equations produce a sequence of approximate ...
Abstract. The three-term Lanczos process for a symmetric matrix leads to bases for Krylov subspaces ...