DocumentCode
2532896
Title
A Parallel Refined Jacobi-Davidson Method for Quadratic Eigenvalue Problems
Author
Wang, Shunxu
Author_Institution
Coll. of Sci., Huaihai Inst. of Technol., Lianyungang, China
fYear
2010
fDate
18-20 Dec. 2010
Firstpage
111
Lastpage
115
Abstract
This paper presents a parallel refined Jacobi-Davidson method for computing extreme eigenpairs of quadratic eigenvalue problems. The method directly computes the refined Ritz pairs in the projection subspace, and expands the subspace by the solution of the correction equation. Combining with the restarting scheme, the method can solve several eigenpairs of quadratic eigenvalue problems. The numerical experiments on a parallel computer show that the parallel refined Jacobi-Davidson method for computing quadratic eigenvalue problems is very effective.
Keywords
eigenvalues and eigenfunctions; mathematics computing; parallel processing; Ritz pairs; extreme eigenpairs; parallel computer; parallel refined Jacobi Davidson method; quadratic eigenvalue problems; Approximation methods; Eigenvalues and eigenfunctions; Equations; Integrated circuits; Jacobian matrices; Matrix decomposition; Parallel processing; Jacobi-Davidson method; Parallel algorithm; Quadratic eigenvalue problems; Refined method;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel Architectures, Algorithms and Programming (PAAP), 2010 Third International Symposium on
Conference_Location
Dalian
Print_ISBN
978-1-4244-9482-8
Type
conf
DOI
10.1109/PAAP.2010.62
Filename
5715071
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