Abstract
In the present paper, we propose a hybrid parallel method for large sparse eigenvalue problems in a grid computing environment. A moment-based method that finds several eigenvalues and their corresponding eigenvectors in a given domain is used. This method is suitable for master-worker type parallel programming models. In order to improve the parallel efficiency of the method, we propose a hybrid implementation using a GridRPC system Ninf-G and MPI. We examined the performance of the proposed method in an environment where several PC clusters are used.
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Sakurai, T., Kodaki, Y., Umeda, H., Inadomi, Y., Watanabe, T., Nagashima, U. (2006). A Hybrid Parallel Method for Large Sparse Eigenvalue Problems on a Grid Computing Environment Using Ninf-G/MPI. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2005. Lecture Notes in Computer Science, vol 3743. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11666806_50
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DOI: https://doi.org/10.1007/11666806_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31994-8
Online ISBN: 978-3-540-31995-5
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