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On the Use of a Genetic Algorithm in High Performance Computer Benchmark Tuning

Abstract : The High-Performance Linpack (HPL) [14] package is a reference benchmark used worldwide to evaluate high-performance computing platforms. Adjustment of HPLpsilas seventeen tuning parameters to achieve maximum performance is a time-consuming task that must be performed by hand. In this paper, we show how a genetic algorithm may be exploited to automatically determine the best parameters possible to maximize the future results of the benchmark. Indeed we propose a GA based approach, even if we do not really specify a particular GA as our investigation relies on the Acovea framework [11], which managed repeated runs of the benchmark to explore the very large space of parameter combinations on the test-case cluster. This work opens the possibility of creating a fully-automatic benchmark tuning tool.
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Submitted on : Tuesday, April 3, 2012 - 1:44:24 PM
Last modification on : Monday, May 4, 2020 - 11:39:40 AM


  • HAL Id : hal-00684874, version 1



Dominic Dunlop, Sébastien Varette, Pascal Bouvry. On the Use of a Genetic Algorithm in High Performance Computer Benchmark Tuning. Proceedings of the IEEE International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS'08), Jun 2008, Edinburgh, United Kingdom. ⟨hal-00684874⟩



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