Applications involving large sparse nonsymmetric linear systems encourage parallel implementations of robust iterative solution methods, such as GMRES(k). Two parallel versions of GMRES(k) based on different data distributions and using Householder reflections in the orthogonalization phase, and variations of these which adapt the restart value k, are analyzed with respect to scalability (their ability to maintain fixed efficiency with an increase in problem size and number of processors).A theoretical algorithm-machine model for scalability is derived and validated by experiments on three parallel computers, each with different machine characteristics
GMRES(m) method, the restarted version of the GMRES (generalized minimal residual) method, is on...
International audienceGrid computing focuses on making use of a very large amount of resources from ...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
International audienceScientific applications very often rely on solving one or more linear systems....
The GMRES iterative method is widely used as Krylov subspace accelerator for solving sparse linear s...
AbstractThe Flexible Generalized Minimal Residual method (FGMRES) is an attractive iterative solver ...
GMRES(k) is widely used for solving nonsymmetric linear systems. However, it is inadequate either w...
GMRES(k) is widely used for solving nonsymmetric linear systems. However, it is inadequate either wh...
Linearization of the non-linear systems arising from fully implicit schemes in computational fluid...
The Generalized Minimum Residual (GMRES) iterative method and variations of it are frequently used f...
Many scientific and industrial problems need the resolution of nonsymmetric linear systems of large ...
International audienceKrylov methods such as GMRES are efficient iterative methods to solve large sp...
Krylov methods provide a fast and highly parallel numerical tool for the iterative solution of many ...
International audienceIn this paper, we revisit the Krylov multisplitting algorithm presented in Hua...
In the Generalized Minimal Residual Method (GMRES), the global all-to-all communication re- quired i...
GMRES(m) method, the restarted version of the GMRES (generalized minimal residual) method, is on...
International audienceGrid computing focuses on making use of a very large amount of resources from ...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
International audienceScientific applications very often rely on solving one or more linear systems....
The GMRES iterative method is widely used as Krylov subspace accelerator for solving sparse linear s...
AbstractThe Flexible Generalized Minimal Residual method (FGMRES) is an attractive iterative solver ...
GMRES(k) is widely used for solving nonsymmetric linear systems. However, it is inadequate either w...
GMRES(k) is widely used for solving nonsymmetric linear systems. However, it is inadequate either wh...
Linearization of the non-linear systems arising from fully implicit schemes in computational fluid...
The Generalized Minimum Residual (GMRES) iterative method and variations of it are frequently used f...
Many scientific and industrial problems need the resolution of nonsymmetric linear systems of large ...
International audienceKrylov methods such as GMRES are efficient iterative methods to solve large sp...
Krylov methods provide a fast and highly parallel numerical tool for the iterative solution of many ...
International audienceIn this paper, we revisit the Krylov multisplitting algorithm presented in Hua...
In the Generalized Minimal Residual Method (GMRES), the global all-to-all communication re- quired i...
GMRES(m) method, the restarted version of the GMRES (generalized minimal residual) method, is on...
International audienceGrid computing focuses on making use of a very large amount of resources from ...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...