DocumentCode
2572513
Title
A Parallel Refined Block Arnoldi Algorithm for Large Unsymmetric Matrices
Author
Zhao, Tao ; Chi, Xuebin ; Jiang, Jinrong ; Liu, Jun ; Lu, Zhonghua
Author_Institution
Supercomput. Center, Chinese Acad. of Sci., Beijing, China
fYear
2009
fDate
25-27 June 2009
Firstpage
678
Lastpage
682
Abstract
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.
Keywords
Chebyshev approximation; eigenvalues and eigenfunctions; iterative methods; parallel algorithms; sparse matrices; Chebyshev iteration; eigenvalues; large sparse unsymmetric matrix; parallel refined block Arnoldi algorithm; parallel refined block methods; Acceleration; Chebyshev approximation; Clustering algorithms; Computer networks; Concurrent computing; Convergence; Eigenvalues and eigenfunctions; High performance computing; Iterative algorithms; Parallel processing; block Arnoldi; parallel algorithm; refined strategy;
fLanguage
English
Publisher
ieee
Conference_Titel
High Performance Computing and Communications, 2009. HPCC '09. 11th IEEE International Conference on
Conference_Location
Seoul
Print_ISBN
978-1-4244-4600-1
Electronic_ISBN
978-0-7695-3738-2
Type
conf
DOI
10.1109/HPCC.2009.20
Filename
5167063
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