This work discusses the design of efficient algorithms for solving symmetric indefinite linear systems arising from FEM approximation of PDEs. The distinctive feature of the preconditioned MINRES solver that is used here is the incorporation of error control in the ‘natural norm’ in combination with an effective a posteriori estimator for the PDE approximation error. This leads to a robust and optimal blackbox stopping criterion: the iteration is terminated as soon as the algebraic error is insignificant compared to the approximation error
Iterative solution methods provide the only feasible alternative to direct methods for very large sc...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
Every Newton step in an interior-point method for optimization requires a solution of a symmetric in...
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 indefinite l...
We discuss the design and implementation of a suite of functions for solving symmetric indefinite l...
We discuss the design and implementation of a suite of functions for solving symmetric indefi-nite l...
The central theme of this thesis is the design of optimal balanced black-box stopping criteria in it...
10.1007/s10589-006-9006-8Computational Optimization and Applications362-3221-247CPPP
We propose a class of preconditioners for symmetric linear systems arising from numerical analysis a...
Abstract. We introduce a novel strategy for constructing symmetric positive definite (SPD) precondit...
AbstractIn this paper, we study the direct solvers for the linear system Ax=b, where A is symmetric ...
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...
Abstract. We consider large scale sparse linear systems in saddle point form. A natural property of ...
Iterative solution methods provide the only feasible alternative to direct methods for very large sc...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
Every Newton step in an interior-point method for optimization requires a solution of a symmetric in...
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 indefinite l...
We discuss the design and implementation of a suite of functions for solving symmetric indefinite l...
We discuss the design and implementation of a suite of functions for solving symmetric indefi-nite l...
The central theme of this thesis is the design of optimal balanced black-box stopping criteria in it...
10.1007/s10589-006-9006-8Computational Optimization and Applications362-3221-247CPPP
We propose a class of preconditioners for symmetric linear systems arising from numerical analysis a...
Abstract. We introduce a novel strategy for constructing symmetric positive definite (SPD) precondit...
AbstractIn this paper, we study the direct solvers for the linear system Ax=b, where A is symmetric ...
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...
Abstract. We consider large scale sparse linear systems in saddle point form. A natural property of ...
Iterative solution methods provide the only feasible alternative to direct methods for very large sc...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
Every Newton step in an interior-point method for optimization requires a solution of a symmetric in...