
doi: 10.1007/bf01388686
We describe a block version of Arnoldi's method for computing a few eigenvalues with largest or smallest real parts. The method is accelerated via Chebyshev iteration and a procedure is developed to identify the optimal ellipse which encloses the spectrum. A parallel implementation of this method is investigated on the eight processor Alliant FX/80. Numerical results and comparisons with simultaneous iteration on some Harwell-Boeing matrices are reported.
Numerical computation of eigenvalues and eigenvectors of matrices, 510.mathematics, sparse matrices, Arnoldi's method, eigenvalues, eigenvectors, Parallel numerical computation, Chebyshev iteration, numerical results, parallel computation, Article
Numerical computation of eigenvalues and eigenvectors of matrices, 510.mathematics, sparse matrices, Arnoldi's method, eigenvalues, eigenvectors, Parallel numerical computation, Chebyshev iteration, numerical results, parallel computation, Article
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 31 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
