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Design and performance evaluation of a distributed eigenvalue solver on a workstation cluster

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5 Author(s)
Trefftz, C. ; Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA ; Huang, C.C. ; McKinley, P.K. ; Li, T.Y.
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Clusters of high-performance workstations are emerging as promising platforms for parallel scientific computing. The paper describes an eigenvalue solver for symmetric tridiagonal matrices, as implemented on a cluster of workstations using two different interprocess communication packages, PVM and P4. The algorithm is based on the split-merge technique, which uses Laguerre's iteration and exploits the separation property of rank two splitting in order to create subtasks that can be solved independently. A performance study that compares the distributed, parallel split-merge algorithm to a parallel version of the well-known bisection algorithm, over standard matrix types, demonstrates the performance advantage of the new algorithm and its cluster implementation

Published in:

Distributed Computing Systems, 1994., Proceedings of the 14th International Conference on

Date of Conference:

21-24 Jun 1994

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