Accelerating Eigenvector Computation in the Nonsymmetric Eigenvalue Problem

TitleAccelerating Eigenvector Computation in the Nonsymmetric Eigenvalue Problem
Publication TypeConference Paper
Year of Publication2014
AuthorsGates, M., A. Haidar, and J. Dongarra
Conference NameVECPAR 2014
Date Published06-2014
Conference LocationEugene, OR
Abstract

In the nonsymmetric eigenvalue problem, work has focused on the Hessenberg reduction and QR iteration, using efficient algorithms and fast, Level 3 BLAS routines. Comparatively, computation of eigenvectors performs poorly, limited to slow, Level 2 BLAS performance with little speedup on multi-core systems. It has thus become a dominant cost in the eigenvalue problem. To address this, we present improvements for the eigenvector computation to use Level 3 BLAS where applicable and parallelize the remaining triangular solves, achieving good parallel scaling and accelerating the overall eigenvalue problem more than three-fold.