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Journal of Signal Processing Systems

, Volume 90, Issue 4, pp 537–570 | Cite as

Comparing Three Clustering-based Scheduling Methods for Energy-Aware Rapid Design of MP2SoCs

  • Manel AmmarEmail author
  • Mouna Baklouti
  • Maxime Pelcat
  • Karol Desnos
  • Mohamed Abid
Article
  • 151 Downloads

Abstract

In recent years, the Electronic Design Automation (EDA) community shifted spotlights from performance to energy efficiency. Consequently, energy consumption becomes a key criterion to take into consideration during Design Space Exploration (DSE). Finding a trade-off between energy consumption and performance early in the design flow in order to satisfy time-to-market is a design challenge of EDA tools. In this paper, we propose the Energy-aWAre Rapid Design of MP2SoC (EWARDS) framework. The EWARDS framework aims at exploring, at design time, the performance and energy capabilities of modern Massively Parallel Multi-Processors System-on-Chip (MP2SoC). The key contribution of the proposed framework is the implementation of an energy-aware scheduling process, named P R E E S M P E , that combines state-of-the-art power management techniques together with Clustering-based Scheduling. The scheduling process is integrated into a Model-Driven Engineering (MDE)-based DSE approach to optimize both performance and energy efficiency in MP2SoC. Moreover, EWARDS extends the Modeling and Analysis of Real-Time and Embedded systems (MARTE) profile with power aspects of MP2SoC systems providing a high-level design entry. To demonstrate the efficiency of the proposed approach, we conducted experiments using the H.263 codec and the FFT algorithm. The obtained results demonstrate that the energy-aware scheduling process can effectively save energy in MP2SoC systems. They also confirmed that our MDE-based approach accelerates the DSE process while generating energy-efficient design decisions.

Keywords

EWARDS Energy-aware design-space exploration MP2SoC Model-driven engineering PREESM Scheduling Power MARTE 

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Manel Ammar
    • 1
    Email author
  • Mouna Baklouti
    • 1
  • Maxime Pelcat
    • 2
  • Karol Desnos
    • 2
  • Mohamed Abid
    • 1
  1. 1.CES LaboratoryNational Engineering School of SfaxSfaxTunisia
  2. 2.IETR, INSA Rennes, CNRS UMR 6164UEBRennesFrance

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