%0 Conference Paper %B VECPAR 2014 %D 2014 %T Accelerating Eigenvector Computation in the Nonsymmetric Eigenvalue Problem %A Mark Gates %A Azzam Haidar %A Jack Dongarra %X 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. %B VECPAR 2014 %C Eugene, OR %8 2014-06 %G eng