AbstractA new reordered formulation of the preconditioned BiCGStab iterative method for the system of linear equations with large sparse nonsymmetric matrix is presented. The algorithm is reformulated in order to improve the efficiency on distributed memory computer systems. It allows to avoid all global synchronization points of the inner product operations. The order of computations permits to overlap the communication time of the inner products by the preconditioning computations. The efficiency of the implemented method with the algebraic multigrid preconditioner is demonstrated by the scalability results for the MPI and the hybrid (MPI +SHM) programming models
Abstract. In this paper we present a communication avoiding ILU0 preconditioner for solving large li...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
AbstractA new reordered formulation of the preconditioned BiCGStab iterative method for the system o...
For the solution of large sparse systems of linear equations with general non-Hermitian coefficient ...
This dissertation deals mainly with the design, implementation, and analysis of efficient iterative ...
We consider Krylov subspace methods for solving a linear system of equations on parallel computer wi...
AbstractThis paper introduces several strategies to deal with pivot blocks in multi-level block inco...
Cette thèse traite d une nouvelle classe de préconditionneurs qui ont pour but d accélérer la résolu...
Summarization: In this paper, which extends and concludes our work in [3, 4], we deal with the probl...
In this paper we present a communication avoiding ILU0 preconditioner for solving large linear syste...
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradi...
International audienceKrylov methods such as GMRES are efficient iterative methods to solve large sp...
ML(n)BiCGStab is a Krylov subspace method for the solution of large, sparse and non-symmetric linear...
. The efficient solution of irregular sparse linear systems on a distributed memory parallel compute...
Abstract. In this paper we present a communication avoiding ILU0 preconditioner for solving large li...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...
AbstractA new reordered formulation of the preconditioned BiCGStab iterative method for the system o...
For the solution of large sparse systems of linear equations with general non-Hermitian coefficient ...
This dissertation deals mainly with the design, implementation, and analysis of efficient iterative ...
We consider Krylov subspace methods for solving a linear system of equations on parallel computer wi...
AbstractThis paper introduces several strategies to deal with pivot blocks in multi-level block inco...
Cette thèse traite d une nouvelle classe de préconditionneurs qui ont pour but d accélérer la résolu...
Summarization: In this paper, which extends and concludes our work in [3, 4], we deal with the probl...
In this paper we present a communication avoiding ILU0 preconditioner for solving large linear syste...
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradi...
International audienceKrylov methods such as GMRES are efficient iterative methods to solve large sp...
ML(n)BiCGStab is a Krylov subspace method for the solution of large, sparse and non-symmetric linear...
. The efficient solution of irregular sparse linear systems on a distributed memory parallel compute...
Abstract. In this paper we present a communication avoiding ILU0 preconditioner for solving large li...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
This article surveys preconditioning techniques for the iterative solution of large linear systems, ...