We address the hard question of efficient use on parallel platforms, of incomplete factorization preconditioning techniques for solving large and sparse linear systems by Krylov subspace methods. A novel parallelization strategy based on pseudo-overlapped subdomains is explored. This results in efficient parallelizable preconditioners. Numerical results give evidence that high performance can be achieved. © 2001 Elsevier Science B.V.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
e inner products, vector updates and matrix vector product are easily parallelized and vectorized. T...
Factorization algorithms based on threshold incomplete LU factorization have been found to be quite ...
We address the hard question of efficient use on parallel platforms, of incomplete factorization p...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
Abstract. Incomplete factorization preconditioners such as ILU, ILUT and MILU are well-known robust ...
AbstractWe design, analyse and test a class of incomplete orthogonal factorization preconditioners c...
International audienceSolving large sparse linear systems by iterative methods has often been quite ...
We review current methods for preconditioning systems of equations for their solution using iterativ...
Two general parallel incomplete factorization strategies are investigated. The techniques may be int...
A class of parallel incomplete factorization preconditionings for the solution of large linear syste...
Two general parallel incomplete factorization strategies are investigated. The techniques may be i...
We present a class of parallel preconditioning strategies built on a multilevel block incomplete LU ...
International audienceThe purpose of our work is to provide a method which exploits the parallel blo...
A class of parallel incomplete factorization preconditionings for the solution of large linear sys...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
e inner products, vector updates and matrix vector product are easily parallelized and vectorized. T...
Factorization algorithms based on threshold incomplete LU factorization have been found to be quite ...
We address the hard question of efficient use on parallel platforms, of incomplete factorization p...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
Abstract. Incomplete factorization preconditioners such as ILU, ILUT and MILU are well-known robust ...
AbstractWe design, analyse and test a class of incomplete orthogonal factorization preconditioners c...
International audienceSolving large sparse linear systems by iterative methods has often been quite ...
We review current methods for preconditioning systems of equations for their solution using iterativ...
Two general parallel incomplete factorization strategies are investigated. The techniques may be int...
A class of parallel incomplete factorization preconditionings for the solution of large linear syste...
Two general parallel incomplete factorization strategies are investigated. The techniques may be i...
We present a class of parallel preconditioning strategies built on a multilevel block incomplete LU ...
International audienceThe purpose of our work is to provide a method which exploits the parallel blo...
A class of parallel incomplete factorization preconditionings for the solution of large linear sys...
A popular class of preconditioners is known as incomplete factorizations. They can be thought of as ...
e inner products, vector updates and matrix vector product are easily parallelized and vectorized. T...
Factorization algorithms based on threshold incomplete LU factorization have been found to be quite ...