Automatic performance tuning for the multi-section with multiple eigenvalues method for symmetric tridiagonal eigenproblems

Authors:
Takahiro Katagiri;Christof Vömel;James W. Demmel
Affiliations:
Computer Science Division, University of California, Berkeley, Berkeley, CA and Graduate School of Information Systems, The University of Electro-Communications, Choufu-shi, Tokyo, Japan;Computer Science Division, University of California, Berkeley, Berkeley, CA;Computer Science Division, University of California, Berkeley, Berkeley, CA
Venue:
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Year:
2006

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Abstract

We propose multisection for the multiple eigenvalues (MME) method for determining the eigenvalues of symmetric tridiagonal matrices. We also propose a method using runtime optimization, and show how to optimize its performance by dynamically selecting the implementation parameters. Performance results using a Hitachi SR8000 supercomputer with eight processors per node yield (1) up to 6.3x speedup over a conventional multisection method, and (2) up to 1.47x speedup over a statically optimized MME method.