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Binding Performance and Power of Dense Linear Algebra Operations

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5 Author(s)
Barreda, M. ; Depto. de Ing. y Cienc. de Comput., Univ. Jaume I, Castellon, Spain ; Dolz, M.F. ; Mayo, R. ; Quintana-Orti, E.S.
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In this paper we combine a powerful tracing framework with a power measurement setup to perform a visual analysis of the computational performance and the power consumption of tuned implementations for three key dense linear algebra operations: the LU factorization, the Cholesky factorization, and the reduction to tridiagonal form. Our results using 6 and 12 cores of an AMD Opteron-based platform reveal the serial/concurrent phases of the algorithms, and their connection to periods of low/high power consumption, as well as the linear dependency between execution time and energy for this class of operations.

Published in:

Parallel and Distributed Processing with Applications (ISPA), 2012 IEEE 10th International Symposium on

Date of Conference:

10-13 July 2012

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