Abstract | ||
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The paper discusses the implementation of a parallel algorithm to compute the eigenvalues and eigenvectors of a real symmetric matrix on a mesh multicomputer. The algorithm uses the one-sided Jacobi method and a two-dimensional organization of the nodes. It is aimed at reducing the communication cost incurred by one-dimensional algorithms found in the literature. The performance of the proposed algorithm on a squared 2D/3D mesh multicomputer is assessed through simple analytical models of execution time. The models show that the performance improvement over one-dimensional algorithms can be very noticeable, specially for a large number of nodes. |
Year | DOI | Venue |
---|---|---|
2001 | 10.1016/S0167-8191(01)00084-9 | Parallel Computing |
Keywords | Field | DocType |
one-sided jacobi method,mesh multicomputer,eigenvalues and eigenvectors,one-dimensional and two-dimensional algorithms,jacobi orderings,symmetric matrix,jacobi method,parallel algorithm | Jacobi rotation,Polygon mesh,Jacobi method,Computer science,Parallel algorithm,Parallel computing,Jacobi eigenvalue algorithm,Symmetric matrix,Theoretical computer science,Eigenvalues and eigenvectors,Performance improvement | Journal |
Volume | Issue | ISSN |
27 | 9 | Parallel Computing |
Citations | PageRank | References |
2 | 0.51 | 4 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Dolors Royo Valles | 1 | 60 | 7.20 |
Miguel Valero-García | 2 | 59 | 9.01 |
Antonio González | 3 | 3178 | 229.66 |