Simultaneous variation-aware architecture exploration and task scheduling for MPSoC energy minimization

  • Authors:
  • Mahmoud Momtazpour;Mahboobeh Ghorbani;Maziar Goudarzi;Esmaeil Sanaei

  • Affiliations:
  • Sharif University of Technology, Tehran, Iran;Sharif University of Technology, Tehran, Iran;Sharif University of Technology, Tehran, Iran;Sharif University of Technology, Tehran, Iran

  • Venue:
  • Proceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI
  • Year:
  • 2011

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Abstract

In nanometer-scale process technologies, the effects of process variations are observed in Multiprocessor System-on-Chips (MPSoC) in terms of variations in frequencies and leakage powers among the processors on the same chip as well as across different chips of the same design. Traditionally, worst-case values are assumed for these parameters and then a deterministic optimization technique is applied to the MPSoC application under design. We show that such worst-case-based approaches are not optimal with the increasing variation observed at system-level, and instead, statistical approaches should be employed. We consider the problem of simultaneously choosing MPSoC architecture and task allocation for energy optimization under a given performance constraint. Our experimental results on E3S benchmark suite show that the proposed statistical optimization technique can achieve 33.7% improvement on average over conventional worst-case-based techniques and up to 21.7 % improvement over best previously proposed statistical analysis technique.