AbstractWe present a parallel hybrid asynchronous method to solve large sparse linear systems by the use of a large parallel machine. This method combines a parallel GMRES(m) algorithm with the least squares method that needs some eigenvalues obtained from a parallel Arnoldi algorithm. All of the algorithms run on different processors of an IBM SP3 or IBM SP4 computer simultaneously. This implementation of this hybrid method allows us to take advantage of the parallelism available and to accelerate the convergence by decreasing considerably the number of iterations
The solution of large sparse linear systems is often the most time-consuming part of many science an...
This thesis presents a set of routines that aim at solving large linear systems on parallel computer...
We are interested in solving large sparse systems of linear equations in parallel. Computing the sol...
International audienceGrid computing focuses on making use of a very large amount of resources from ...
International audienceGrid computing in general is a special type of parallel computing. It intends ...
Many scientific and industrial problems need the resolution of nonsymmetric linear systems of large ...
AbstractA method for simultaneous solution of large and sparse linearized equation sets and the corr...
Nous étudions dans cette thèse une méthode hybride de résolution des systèmes linéaires GMRES/LS-Arn...
Nous nous intéressons à la résolution en parallèle de système d’équations linéaires creux et de larg...
We consider the challenge of solving large scale sparse linear systems arising from different applic...
AbstractIn this paper we present two efficient algorithms for the parallel solution of n × n dense l...
It is important to have a fast, robust and scalable algorithm to solve a sparse linear system AX=B. ...
Iterative methods for solving large sparse systems of linear equations are widely used in many HPC a...
Large-scale scientific applications and industrial simulations are nowadays fully integrated in many...
The solution of large sparse linear systems is often the most time-consuming part of many science an...
The solution of large sparse linear systems is often the most time-consuming part of many science an...
This thesis presents a set of routines that aim at solving large linear systems on parallel computer...
We are interested in solving large sparse systems of linear equations in parallel. Computing the sol...
International audienceGrid computing focuses on making use of a very large amount of resources from ...
International audienceGrid computing in general is a special type of parallel computing. It intends ...
Many scientific and industrial problems need the resolution of nonsymmetric linear systems of large ...
AbstractA method for simultaneous solution of large and sparse linearized equation sets and the corr...
Nous étudions dans cette thèse une méthode hybride de résolution des systèmes linéaires GMRES/LS-Arn...
Nous nous intéressons à la résolution en parallèle de système d’équations linéaires creux et de larg...
We consider the challenge of solving large scale sparse linear systems arising from different applic...
AbstractIn this paper we present two efficient algorithms for the parallel solution of n × n dense l...
It is important to have a fast, robust and scalable algorithm to solve a sparse linear system AX=B. ...
Iterative methods for solving large sparse systems of linear equations are widely used in many HPC a...
Large-scale scientific applications and industrial simulations are nowadays fully integrated in many...
The solution of large sparse linear systems is often the most time-consuming part of many science an...
The solution of large sparse linear systems is often the most time-consuming part of many science an...
This thesis presents a set of routines that aim at solving large linear systems on parallel computer...
We are interested in solving large sparse systems of linear equations in parallel. Computing the sol...