Extracting the optimal sampling frequency of applications using spectral analysis

  • Authors:

  • Marc Casas;Harald Servat;Rosa M. Badia;Jesús Labarta

  • Affiliations:

  • Lawrence Livermore National Laboratory (LLNL), Box 808, L-561 Livermore, CA94551-0808, USA;Barcelona Supercomputing Center (BSC), Barcelona, Spain;Barcelona Supercomputing Center (BSC), Barcelona, Spain;Technical University of Catalonia (UPC), Barcelona, Spain

  • Venue:
  • Concurrency and Computation: Practice & Experience
  • Year:
  • 2011

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Abstract

The research community have agreed on several applications as benchmarks to evaluate the adequateness of architectures and high performance computing infrastructures. The performance of these benchmarks is used to determine the weaknesses and strengths of novel designs. Therefore, the performance evaluation of benchmarks is a key factor in the process of designing new architectures. In this paper, we propose a new method based on spectral analysis that allows to perform an automatic analysis of benchmarks' executions. The output of the new method is a representative segment of the benchmarks' executions. Given the nature of the method, the optimal sampling interval length of applications is obtained. This method complements and improves existing techniques focused on the reduction of the application's instruction execution stream of sequential benchmarks and enables the extraction of significant performance information of parallel benchmarks without executing the whole application. The results obtained with the SPEC CPU2000 and the NAS Parallel Benchmarks demonstrate the efficiency and benefits of the approach. Copyright © 2011 John Wiley & Sons, Ltd.