A Parallel Refined Block Arnoldi Algorithm for Large Unsymmetric Matrices

This paper proposed a parallel refined block Arnoldi method for computing a few eigenvalues with largest or smallest real parts. The method accelerated by Chebyshev iteration is also investigated. We report some numerical results and compare the parallel refined block methods with single vector coun...

Full description

Saved in:
Bibliographic Details
Main Authors: Tao Zhao, Xuebin Chi, Jinrong Jiang, Jun Liu, Zhonghua Lu
Format: Conference Proceeding
Language:English
Subjects:
Acceleration
block Arnoldi
Chebyshev approximation
Clustering algorithms
Computer networks
Concurrent computing
Convergence
Eigenvalues and eigenfunctions
High performance computing
Iterative algorithms
parallel algorithm
Parallel processing
refined strategy
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposed a parallel refined block Arnoldi method for computing a few eigenvalues with largest or smallest real parts. The method accelerated by Chebyshev iteration is also investigated. We report some numerical results and compare the parallel refined block methods with single vector counterparts. The results show that the proposed method is more efficient than single vector counterparts.
DOI:10.1109/HPCC.2009.20