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A graph based method for generating the fiedler vector of irregular problems

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Parallel and Distributed Processing (IPPS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1586))

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Abstract

In this paper we present new algorithms for spectral graph partitioning. Previously, the best partitioning methods were based on a combination of Combinatorial algorithms and application of the Lanczos method when the graph allows this method to be cheap enough. Our new algorithms are purely spectral. They calculate the Fiedler vector of the original graph and use the information about the problem in the form of a preconditioner for the graph Laplacian. In addition, we use a favorable subspace for starting the Davidson algorithm and reordering of variables for locality of memory references.

This research was supported by NSF grant ASC-9528912, and currently by NSF/DARPA DMS-9874015

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José Rolim Frank Mueller Albert Y. Zomaya Fikret Ercal Stephan Olariu Binoy Ravindran Jan Gustafsson Hiroaki Takada Ron Olsson Laxmikant V. Kale Pete Beckman Matthew Haines Hossam ElGindy Denis Caromel Serge Chaumette Geoffrey Fox Yi Pan Keqin Li Tao Yang G. Chiola G. Conte L. V. Mancini Domenique Méry Beverly Sanders Devesh Bhatt Viktor Prasanna

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© 1999 Springer-Verlag

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Holzrichter, M., Oliveira, S. (1999). A graph based method for generating the fiedler vector of irregular problems. In: Rolim, J., et al. Parallel and Distributed Processing. IPPS 1999. Lecture Notes in Computer Science, vol 1586. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0097982

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  • DOI: https://doi.org/10.1007/BFb0097982

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  • Print ISBN: 978-3-540-65831-3

  • Online ISBN: 978-3-540-48932-0

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