|Title||Accelerating Eigenvector Computation in the Nonsymmetric Eigenvalue Problem|
|Publication Type||Conference Paper|
|Year of Publication||2014|
|Authors||Gates, M., A. Haidar, and J. Dongarra|
|Conference Name||VECPAR 2014|
|Conference Location||Eugene, OR|
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.
Accelerating Eigenvector Computation in the Nonsymmetric Eigenvalue Problem