Rational Krylov methods are applicable to a wide range of scientific computing problems, and the rational Arnoldi algorithm is a commonly used procedure for computing an orthonormal basis of a rational Krylov space. Typically, the computationally most expensive component of this algorithm is the solution of a large linear system of equations at each iteration. We explore the option of solving several linear systems simultaneously, thus constructing the rational Krylov basis in parallel. If this is not done carefully, the basis being orthogonalized may become badly conditioned, leading to numerical instabilities in the orthogonalization process. We introduce the new concept of continuation pairs which gives rise to a near-optimal paralleliza...
This dissertation focuses on efficiently forming reduced-order models for large, linear dynamic syst...
Rational Krylov is an extension of the Lanczos or Arnoldi eigenvalue algorithm where several shifts ...
Matrix functions are a central topic of linear algebra, and problems of their numerical approximatio...
Rational Krylov methods are applicable to a wide range of scientific computing problems, and the rat...
Numerical methods related on Krylov subspaces are widely used in large sparse numerical linear algeb...
Numerical methods based on rational Krylov spaces have become an indispensable tool of scientific co...
Numerical methods related to Krylov subspaces are widely used in large sparse numerical linear algeb...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
Rational Krylov sequences were introduced over 30 years ago by Ruhe (1984) and have been an active s...
International audienceMany numerical simulations end up on a problem of linear algebra involving an ...
Numerical methods related on Krylov subspaces are widely used in large sparse numerical linear algeb...
The block version of the rational Arnoldi method is a widely used procedure for generating an orthon...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
e inner products, vector updates and matrix vector product are easily parallelized and vectorized. T...
The rational Arnoldi process is a popular method for the computation of a few eigenvalues of a large...
This dissertation focuses on efficiently forming reduced-order models for large, linear dynamic syst...
Rational Krylov is an extension of the Lanczos or Arnoldi eigenvalue algorithm where several shifts ...
Matrix functions are a central topic of linear algebra, and problems of their numerical approximatio...
Rational Krylov methods are applicable to a wide range of scientific computing problems, and the rat...
Numerical methods related on Krylov subspaces are widely used in large sparse numerical linear algeb...
Numerical methods based on rational Krylov spaces have become an indispensable tool of scientific co...
Numerical methods related to Krylov subspaces are widely used in large sparse numerical linear algeb...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
Rational Krylov sequences were introduced over 30 years ago by Ruhe (1984) and have been an active s...
International audienceMany numerical simulations end up on a problem of linear algebra involving an ...
Numerical methods related on Krylov subspaces are widely used in large sparse numerical linear algeb...
The block version of the rational Arnoldi method is a widely used procedure for generating an orthon...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
e inner products, vector updates and matrix vector product are easily parallelized and vectorized. T...
The rational Arnoldi process is a popular method for the computation of a few eigenvalues of a large...
This dissertation focuses on efficiently forming reduced-order models for large, linear dynamic syst...
Rational Krylov is an extension of the Lanczos or Arnoldi eigenvalue algorithm where several shifts ...
Matrix functions are a central topic of linear algebra, and problems of their numerical approximatio...