Nonsymmetric Eigenvalue Problems: ScaLAPACK
Computational Routines
This section describes ScaLAPACK routines for solving
nonsymmetric eigenvalue problems, computing the Schur factorization of general
matrices, as well as performing a number of related computational tasks.
To solve a nonsymmetric eigenvalue problem with
ScaLAPACK, you usually need to reduce the matrix to the upper Hessenberg form
and then solve the eigenvalue problem with the Hessenberg matrix obtained.
Table
, as well as routines for solving eigenproblems with Hessenberg
matrices, and multiplying the matrix after reduction.
"Computational Routines for Solving
Nonsymmetric Eigenproblems"
lists ScaLAPACK routines for reducing the matrix to the upper
Hessenberg form by an orthogonal (or unitary) similarity transformation
A
=
QHQ
H