ABSTRACTThis paper presents a new approach to precondition linear systems of the saddle point kind. Specifically we consider block diagonal, block triangular and block indefinite preconditioning techniques on nonsymmetric systems. These preconditioners require the computation of some inverses and we propose to use sparse approximate inverses (SPAI) to construct these approximations. The computation of these inverses involves solving a set of uncoupled least squares problems, which can be easily parallelized on a memory distributed machine. Comparison with other techniques suggests that block diagonal and block triangular preconditioning can be more effective if they are combined with SPAI techniques in the computation of approximate inverse...
[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear sys...
We review current methods for preconditioning systems of equations for their solution using iterativ...
. For a sparse linear system Ax = b, preconditioners of the form C = D + L + U , where D is the blo...
ABSTRACTThis paper presents a new approach to precondition linear systems of the saddle point kind. ...
The efficient parallel solution to large sparse linear systems of equations Ax = b is a central issu...
We investigate the cost of preconditioning when solving large sparse saddlepoint linear systems wit...
Neste trabalho de dissertação apresentaremos uma classe de precondicionadores baseados na aproximaçã...
Iterative methods are currently the solvers of choice for large sparse linear systems of equations. ...
This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A p...
Abstract. We investigate the use of sparse approximate-inverse preconditioners for the iterative sol...
Saddle point problems arise frequently in many applications in science and engineering, including co...
Updating preconditioners for the solution of sequences of large and sparse saddlepoint linear syste...
The class of preconditioning that approximates the inverse of the matrix A is studied in the thesis....
. This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A...
By considering Krylov subspace methods in nonstandard inner products, we develop in this thesis new ...
[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear sys...
We review current methods for preconditioning systems of equations for their solution using iterativ...
. For a sparse linear system Ax = b, preconditioners of the form C = D + L + U , where D is the blo...
ABSTRACTThis paper presents a new approach to precondition linear systems of the saddle point kind. ...
The efficient parallel solution to large sparse linear systems of equations Ax = b is a central issu...
We investigate the cost of preconditioning when solving large sparse saddlepoint linear systems wit...
Neste trabalho de dissertação apresentaremos uma classe de precondicionadores baseados na aproximaçã...
Iterative methods are currently the solvers of choice for large sparse linear systems of equations. ...
This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A p...
Abstract. We investigate the use of sparse approximate-inverse preconditioners for the iterative sol...
Saddle point problems arise frequently in many applications in science and engineering, including co...
Updating preconditioners for the solution of sequences of large and sparse saddlepoint linear syste...
The class of preconditioning that approximates the inverse of the matrix A is studied in the thesis....
. This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A...
By considering Krylov subspace methods in nonstandard inner products, we develop in this thesis new ...
[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear sys...
We review current methods for preconditioning systems of equations for their solution using iterativ...
. For a sparse linear system Ax = b, preconditioners of the form C = D + L + U , where D is the blo...