Numerical methods related on Krylov subspaces are widely used in large sparse numerical linear algebra. Vectors in these subspaces are manipulated through their representation onto orthonormal bases. Nowadays, on serial computers, the method of Arnoldi is considered as a reliable technique for constructing such bases. Unfortunately, this technique is rather inflexible to be efficiently implemented on parallel computers. In this report we examine several parallel and stable algorithms based on the idea of Reichel et al. which retrieve at their completion the same information as the sequential Arnoldi's method. We present timing results obtained from their implementations on the Intel Paragon distributed-memory multiprocessor machine. (Résumé...
Large-scale problems in engineering and science often require the solution of sparse linear algebra ...
Gary Kumfert and Alex Pothen have improved the quality and run time of two ordering algorithms for m...
AbstractThis paper gives improved parallel methods for several exact factorizations of some classes ...
Numerical methods related to Krylov subspaces are widely used in large sparse numerical linear algeb...
Numerical methods related on Krylov subspaces are widely used in large sparse numerical linear algeb...
Rational Krylov methods are applicable to a wide range of scientific computing problems, and the rat...
International audienceMany numerical simulations end up on a problem of linear algebra involving an ...
The paper presents the novel principle on constructing a new class of highly parallel fast stable nu...
e inner products, vector updates and matrix vector product are easily parallelized and vectorized. T...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
For the solution of large sparse systems of linear equations with general non-Hermitian coefficient ...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
We survey general techniques and open problems in numerical linear algebra on parallel architectures...
AbstractWe present randomized algorithms for the solution of some numerical linear algebra problems....
The bulk synchronous parallel (BSP) model promises scalable and portable software for a wide range o...
Large-scale problems in engineering and science often require the solution of sparse linear algebra ...
Gary Kumfert and Alex Pothen have improved the quality and run time of two ordering algorithms for m...
AbstractThis paper gives improved parallel methods for several exact factorizations of some classes ...
Numerical methods related to Krylov subspaces are widely used in large sparse numerical linear algeb...
Numerical methods related on Krylov subspaces are widely used in large sparse numerical linear algeb...
Rational Krylov methods are applicable to a wide range of scientific computing problems, and the rat...
International audienceMany numerical simulations end up on a problem of linear algebra involving an ...
The paper presents the novel principle on constructing a new class of highly parallel fast stable nu...
e inner products, vector updates and matrix vector product are easily parallelized and vectorized. T...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
For the solution of large sparse systems of linear equations with general non-Hermitian coefficient ...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
We survey general techniques and open problems in numerical linear algebra on parallel architectures...
AbstractWe present randomized algorithms for the solution of some numerical linear algebra problems....
The bulk synchronous parallel (BSP) model promises scalable and portable software for a wide range o...
Large-scale problems in engineering and science often require the solution of sparse linear algebra ...
Gary Kumfert and Alex Pothen have improved the quality and run time of two ordering algorithms for m...
AbstractThis paper gives improved parallel methods for several exact factorizations of some classes ...