Scalable eigenvector computation for the non-symmetric eigenvalue problem

Abstract

We present two task-centric algorithms for computing selected eigenvectors of a non-symmetric matrix reduced to real Schur form. Our approach eliminates the sequential phases present in the current LAPACK/ScaLAPACK implementation. We demonstrate the scalability of our implementation on multicore, manycore and distributed memory systems.