Some new restart vectors for explicitly restarted Arnoldi method

Multiple Explicitly Restarted Arnoldi Method for Solving Large Eigenproblems

In this paper we propose a new approach for calculating some eigenpairs of large sparse nonHermitian matrices. This method, called Multiple Explicitly Restarted Arnoldi (MERAM), is particularly well suited for environments that combine different parallel programming paradigms. This technique is based on a multiple use of Explicitly Restarted Arnoldi method and improves its convergence. This tec...

A Comparison Between Parallel Multiple Explicitly Restarted and Explicitly Restarted Block Arnoldi Methods

Evaluation of Acceleration Techniques for the Restarted Arnoldi Method

We present an approach for the acceleration of the restarted Arnoldi iteration for the computation of a number of eigenvalues of the standard eigenproblem Ax = λx. This study applies the Chebyshev polynomial to the restarted Arnoldi iteration and proves that it computes necessary eigenvalues with far less complexity than the QR method. We also discuss the dependence of the convergence rate of t...

Analysis of Accelerating Algorithms for the Restarted Arnoldi Iteration

We present an approach for the acceleration of the restarted Arnoldi iteration for the computation of a number of eigenvalues of the standard eigenproblem Ax = x. This study applies the Chebyshev polynomial to the restarted Arnoldi iteration and proves that it computes necessary eigenvalues with far less complexity than the QR method. We also discuss the dependence of the convergence rate of th...

Implicitly Restarted Arnoldi/lanczos Methods for Large Scale Eigenvalue Calculations

This report provides an introductory overview of the numerical solution of large scale algebraic eigenvalue problems. The main focus is on a class of methods called Krylov subspace projection methods. The Lanczos method is the premier member of this class and the Arnoldi method is a generalization to the nonsymmetric case. A recently developed and very promising variant of the Arnoldi/Lanczos s...

Deflation Techniques for an Implicitly Restarted Arnoldi Iteration

A deeation procedure is introduced that is designed to improve the convergence of an implicitly restarted Arnoldi iteration for computing a few eigenvalues of a large matrix. As the iteration progresses the Ritz value approximations of the eigenvalues of A converge at diierent rates. A numerically stable scheme is introduced that implicitly deeates the converged approximations from the iteratio...