Parallel algorithms for triangularization of large, sparse, and unsymmetric matrices are presented. The method combines the parallel reduction with a new parallel pivoting technique, control over generations of fill-ins and a check for numerical stability, all done in parallel with the work being distributed over the active processes. The parallel technique uses the compatibility relation between pivots to identify parallel pivot candidates and uses the Markowitz number of pivots to minimize fill-in. This technique is not a preordering of the sparse matrix and is applied dynamically as the decomposition proceeds
Texte intégral accessible uniquement aux membres de l'Université de LorraineThis dissertation treats...
Solution of sparse triangular systems of linear equations is a performance bottleneck in many method...
Many linear algebra algorithms require explicit row/column swapping mainly when pivoting operations ...
In this paper it is investigated which pivots may be processed simultaneously when solving a set of ...
This thesis presents a parallel algorithm for the direct LU factorization of general unsymmetric spa...
. Solving large nonsymmetric sparse linear systems on distributed memory multiprocessors is an activ...
[Abstract] We present a parallel algorithm for the QR factorization with column pivoting of a spar...
In this paper we present a new parallel algorithm for the LU decomposition of a general sparse matri...
A few parallel algorithms for solving triangular systems resulting from parallel factorization of sp...
In this paper we present a new parallel algorithm for the LU decomposition of a general sparse matri...
Abstract. A parallel algorithm is presented for the LU decomposition of a general sparse matrix on a...
AbstractCoarse grain parallel codes for solving sparse systems of linear algebraic equations can be ...
Gary Kumfert and Alex Pothen have improved the quality and run time of two ordering algorithms for m...
Abstract. We investigate several ways to improve the performance of sparse LU factorization with par...
We consider direct methods for the numerical solution of linear systems with unsymmetric sparse matr...
Texte intégral accessible uniquement aux membres de l'Université de LorraineThis dissertation treats...
Solution of sparse triangular systems of linear equations is a performance bottleneck in many method...
Many linear algebra algorithms require explicit row/column swapping mainly when pivoting operations ...
In this paper it is investigated which pivots may be processed simultaneously when solving a set of ...
This thesis presents a parallel algorithm for the direct LU factorization of general unsymmetric spa...
. Solving large nonsymmetric sparse linear systems on distributed memory multiprocessors is an activ...
[Abstract] We present a parallel algorithm for the QR factorization with column pivoting of a spar...
In this paper we present a new parallel algorithm for the LU decomposition of a general sparse matri...
A few parallel algorithms for solving triangular systems resulting from parallel factorization of sp...
In this paper we present a new parallel algorithm for the LU decomposition of a general sparse matri...
Abstract. A parallel algorithm is presented for the LU decomposition of a general sparse matrix on a...
AbstractCoarse grain parallel codes for solving sparse systems of linear algebraic equations can be ...
Gary Kumfert and Alex Pothen have improved the quality and run time of two ordering algorithms for m...
Abstract. We investigate several ways to improve the performance of sparse LU factorization with par...
We consider direct methods for the numerical solution of linear systems with unsymmetric sparse matr...
Texte intégral accessible uniquement aux membres de l'Université de LorraineThis dissertation treats...
Solution of sparse triangular systems of linear equations is a performance bottleneck in many method...
Many linear algebra algorithms require explicit row/column swapping mainly when pivoting operations ...