A common approach to solve problems in numerical linear algebra eciently on modern high speed computers is to redesign the classical algorithm which was originally developed for serial computers In this paper we discuss block variants of QR and Jacobi algorithms for the computation of the complete spectral decomposition of symmetric matrices We report on numerical tests which have been performed on a CRAY YMP and an ALLIANT FX/80
It is demonstrated how conventional algorithms for computing the LDU decomposition of a square matri...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If i...
The QR algorithm is an algorithm for computing the spectral de-composition of a symmetric matrix [9]...
In this paper we present a new stable algorithm for the parallel QR-decomposition of ”tall and skinn...
Jacobi techniques for computing the symmetric eigenvalue and singular value decompositions have ach...
A parallel Jacobi-like method for computing the QR-decomposition of an $n \times n$ matrix is propo...
Jacobi-based algorithms have attracted attention as they have a high degree of potential parallelism...
AbstractSystolic arrays have become established in principle, if not yet in practice, as a way of in...
An algorithm is presented for computing the eigenvalues and eigenvectors of an n x n real symmetric...
The purpose of this work is to improve stability and performance of selected matrix decompositions i...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
AbstractA Jacobi-type updating algorithm for the SVD or the URV decomposition is developed, which is...
The Jacobi\u2013Davidson (JD) algorithm was recently proposed for evaluating a number of the eigenva...
Interplay between structured matrices and corresponding systems of polynomials is a classical topic,...
It is demonstrated how conventional algorithms for computing the LDU decomposition of a square matri...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If i...
The QR algorithm is an algorithm for computing the spectral de-composition of a symmetric matrix [9]...
In this paper we present a new stable algorithm for the parallel QR-decomposition of ”tall and skinn...
Jacobi techniques for computing the symmetric eigenvalue and singular value decompositions have ach...
A parallel Jacobi-like method for computing the QR-decomposition of an $n \times n$ matrix is propo...
Jacobi-based algorithms have attracted attention as they have a high degree of potential parallelism...
AbstractSystolic arrays have become established in principle, if not yet in practice, as a way of in...
An algorithm is presented for computing the eigenvalues and eigenvectors of an n x n real symmetric...
The purpose of this work is to improve stability and performance of selected matrix decompositions i...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
AbstractA Jacobi-type updating algorithm for the SVD or the URV decomposition is developed, which is...
The Jacobi\u2013Davidson (JD) algorithm was recently proposed for evaluating a number of the eigenva...
Interplay between structured matrices and corresponding systems of polynomials is a classical topic,...
It is demonstrated how conventional algorithms for computing the LDU decomposition of a square matri...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If i...