Abstract. Motivated by the paper [16], where the authors proposed a method to solve a symmet-ric positive definite (SPD) system Ax = b via a sparse-sparse iterative-based projection method, we extend this method to nonsymmetric linear systems and propose a modified method to con-struct a sparse approximate inverse preconditioner by using the Frobenius norm minimization technique in this paper. Numerical experiments indicate that this new preconditioner appears more robust and takes less time of constructing than the popular parallel sparse approximate inverse preconditioner (PSM) proposed in [6
onditioners, or incomplete LU-decompositions of A [2]. But these preconditioners either lead to unsa...
[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear sys...
The concept of supernodes, originally developed to accelerate direct solution methods for linear sys...
This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A p...
. This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A...
Abstract. We investigate the use of sparse approximate-inverse preconditioners for the iterative sol...
The efficient solution to nonsymmetric linear systems is still an open issue, especially on parallel...
A sparse approximate inverse technique is introduced to solve general sparse linear systems. The spa...
We investigate the use of sparse approximate inverse preconditioners for the iterative solution of l...
The efficient parallel solution to large sparse linear systems of equations Ax = b is a central issu...
The efficient solution to non-symmetric linear systems is still an open issue on parallel computers....
The efficient solution to non-symmetric linear systems is still an open issue on parallel computers....
AbstractKrylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an effici...
Krylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an efficient appr...
AbstractKrylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an effici...
onditioners, or incomplete LU-decompositions of A [2]. But these preconditioners either lead to unsa...
[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear sys...
The concept of supernodes, originally developed to accelerate direct solution methods for linear sys...
This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A p...
. This paper is concerned with a new approach to preconditioning for large, sparse linear systems. A...
Abstract. We investigate the use of sparse approximate-inverse preconditioners for the iterative sol...
The efficient solution to nonsymmetric linear systems is still an open issue, especially on parallel...
A sparse approximate inverse technique is introduced to solve general sparse linear systems. The spa...
We investigate the use of sparse approximate inverse preconditioners for the iterative solution of l...
The efficient parallel solution to large sparse linear systems of equations Ax = b is a central issu...
The efficient solution to non-symmetric linear systems is still an open issue on parallel computers....
The efficient solution to non-symmetric linear systems is still an open issue on parallel computers....
AbstractKrylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an effici...
Krylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an efficient appr...
AbstractKrylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an effici...
onditioners, or incomplete LU-decompositions of A [2]. But these preconditioners either lead to unsa...
[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear sys...
The concept of supernodes, originally developed to accelerate direct solution methods for linear sys...