Evaluation of Subspace Iteration Software for Sparse Nonsymmetric Eigenproblems

摘要

During the last decade there has been a rise in interest in numerical methods forcomputing eigenvalues (and Eigenvectors) of large sparse nonsysmmetric matrices. The research effort is now being accompanied by the development of high-quality mathematical software. One of the methods which has received attention is that of subspace iteration and several software packages implementing subspace iteration algorithms have become available. In this report, as part of an extensive study to evaluate state-of-the-art software for the sparse nonsymmetric eigenproblem, we review subspace iteration software. We look at the key features of the software, the main difference between the packages, and their ease of use. Then, using a wide range of test matrices arising from practical problems, we compare the performance of the codes in terms of storage requirements, execution times, accuracy, and reliability, and consider their suitability for solving large-scale industrial problems.