Dynamic configuration prefetching based on piecewise linear prediction

  • Authors:
  • Adrian Lifa;Petru Eles;Zebo Peng

  • Affiliations:
  • Linköping University, Linköping, Sweden;Linköping University, Linköping, Sweden;Linköping University, Linköping, Sweden

  • Venue:
  • Proceedings of the Conference on Design, Automation and Test in Europe
  • Year:
  • 2013

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Abstract

Modern systems demand high performance, as well as high degrees of flexibility and adaptability. Many current applications exhibit a dynamic and nonstationary behavior, having certain characteristics in one phase of their execution, that will change as the applications enter new phases, in a manner unpredictable at design-time. In order to meet the performance requirements of such systems, it is important to have on-line optimization algorithms, coupled with adaptive hardware platforms, that together can adjust to the run-time conditions. We propose an optimization technique that minimizes the expected execution time of an application by dynamically scheduling hardware prefetches. We use a piecewise linear predictor in order to capture correlations and predict the hardware modules to be reached. Experiments show that the proposed algorithm outperforms the previous state-of-art in reducing the expected execution time by up to 27% on average.