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
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;
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
DOI :
10.1109/HPCC.2009.20
