A standard approach for computing eigenvectors of a non-symmetric matrix reduced to real Schurform relies on a variant of backward substitution. Backward substitution is prone to overflow. To avoid overflow, the LAPACK eigenvector routine DTREVC3 associates every eigenvector with a scaling factor and dynamically rescales an entire eigenvector during the backward substitution such that overflow cannot occur. When many eigenvectors are computed, DTREVC3 applies backward substitution successively for every eigenvector. This corresponds to level-2 BLAS operations and constitutes a bottleneck. This paper redesigns the backward substitution such that the entire computation is cast as tile operations (level-3 BLAS). By replacing LAPACK’s scaling f...
. This paper addresses the question of the form library routine eigenvalue solvers for large--scale ...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
Independent eigenvector computation for a given set of eigenvalues of typical engineering eigenvalue...
A standard approach for computing eigenvectors of a non-symmetric matrix reduced to real Schurform r...
In the nonsymmetric eigenvalue problem, work has focused on the Hessenberg reduction and QR iteratio...
In this paper we discuss the problem of computing eigenvectors for matrices in Schur form using para...
Abstract. Balancing a matrix is a preprocessing step while solving the nonsymmetric eigenvalue probl...
An effective strategy in dense linear algebra is the design of algorithms as tiled algorithms. Tiled...
textThis thesis demonstrates an efficient parallel method of solving the generalized eigenvalue prob...
We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) too...
The central importance of large-scale eigenvalue problems in scientific computation necessitates the...
Abstract. The sequential algorithm of Multiple Relatively Robust Representations, MRRR, can compute ...
Abstract. Bisection is a parallelizable method for finding the eigenvalues of real symmetric tridiag...
Given n × n matrix A, find scalar λ and nonzero vector x such that Ax = λx λ is eigenvalue and x is ...
We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) too...
. This paper addresses the question of the form library routine eigenvalue solvers for large--scale ...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
Independent eigenvector computation for a given set of eigenvalues of typical engineering eigenvalue...
A standard approach for computing eigenvectors of a non-symmetric matrix reduced to real Schurform r...
In the nonsymmetric eigenvalue problem, work has focused on the Hessenberg reduction and QR iteratio...
In this paper we discuss the problem of computing eigenvectors for matrices in Schur form using para...
Abstract. Balancing a matrix is a preprocessing step while solving the nonsymmetric eigenvalue probl...
An effective strategy in dense linear algebra is the design of algorithms as tiled algorithms. Tiled...
textThis thesis demonstrates an efficient parallel method of solving the generalized eigenvalue prob...
We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) too...
The central importance of large-scale eigenvalue problems in scientific computation necessitates the...
Abstract. The sequential algorithm of Multiple Relatively Robust Representations, MRRR, can compute ...
Abstract. Bisection is a parallelizable method for finding the eigenvalues of real symmetric tridiag...
Given n × n matrix A, find scalar λ and nonzero vector x such that Ax = λx λ is eigenvalue and x is ...
We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) too...
. This paper addresses the question of the form library routine eigenvalue solvers for large--scale ...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
Independent eigenvector computation for a given set of eigenvalues of typical engineering eigenvalue...