Elliptic partial differential equations that are used to model physical phenomena give rise to large sparse linear systems. Such systems can be symmetric positive definite and can be solved by the preconditioned conjugate gradients method. In this thesis, we develop support graph preconditioners for symmetric positive definite matrices that arise from the finite element discretization of elliptic partial differential equations. An object oriented code is developed for the construction, integration and application of these preconditioners. Experimental results show that the advantages of support graph preconditioners are retained in the proposed extension to the finite element matrices
We present a new preconditioner for linear systems arising from finite-element discretizations of sc...
This report presents preconditioning techniques for the conjugate gradient method (CG), an iterative...
We propose an automatic preconditioning scheme for large sparse numerical optimization. The strateg...
A relatively new preconditioning technique called support graph preconditioning has many merits over...
preconditioners and a parallel algorithm called supporttree conjugate gradient (STCG) for solving li...
Preconditioned conjugate gradient methods for solving sparse symmetric and positive finite systems o...
91 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.In the second part of the thes...
This paper deals with background and practical experience with preconditioned gradient methods for s...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
This paper describes a preconditioned conjugate gradient method that can be effectively implemented ...
AbstractThe restrictively preconditioned conjugate gradient (RPCG) method for solving large sparse s...
In this paper we introduce LORASC, a robust algebraic preconditioner for solving sparse linear syste...
This report presents preconditioning techniques for the conjugate gradient method (CG), an iterative...
A numerical study of the efficiency of the modified conjugate gradients (MCG) is performed using dif...
Randomized methods are becoming increasingly popular in numerical linear algebra. However, few attem...
We present a new preconditioner for linear systems arising from finite-element discretizations of sc...
This report presents preconditioning techniques for the conjugate gradient method (CG), an iterative...
We propose an automatic preconditioning scheme for large sparse numerical optimization. The strateg...
A relatively new preconditioning technique called support graph preconditioning has many merits over...
preconditioners and a parallel algorithm called supporttree conjugate gradient (STCG) for solving li...
Preconditioned conjugate gradient methods for solving sparse symmetric and positive finite systems o...
91 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.In the second part of the thes...
This paper deals with background and practical experience with preconditioned gradient methods for s...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
This paper describes a preconditioned conjugate gradient method that can be effectively implemented ...
AbstractThe restrictively preconditioned conjugate gradient (RPCG) method for solving large sparse s...
In this paper we introduce LORASC, a robust algebraic preconditioner for solving sparse linear syste...
This report presents preconditioning techniques for the conjugate gradient method (CG), an iterative...
A numerical study of the efficiency of the modified conjugate gradients (MCG) is performed using dif...
Randomized methods are becoming increasingly popular in numerical linear algebra. However, few attem...
We present a new preconditioner for linear systems arising from finite-element discretizations of sc...
This report presents preconditioning techniques for the conjugate gradient method (CG), an iterative...
We propose an automatic preconditioning scheme for large sparse numerical optimization. The strateg...