The efficient solution of large sparse nonsymmetric and complex eigensystems by subspace iteration

This paper presents an efficient solver for the generalized eigenvalue problems of large, sparse, arbitrary real or complex matrices. This solver based on the simplified subspace iteration can efficiently find one or a group of desired eigenvalues and the respective eigenvectors. The statistics and comparison are also presented to show the performance of the sparse matrix solver.<>