Power and Energy Estimations in Model-Based Design

  • Eric Senn
  • Saadia Douhib
  • Dominique Blouin
  • Johann Laurent
  • Skander Turki
  • Jean-Philippe Diguet
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 36)

Abstract

The aim of our works is to provide for methods and tools to quickly estimate the power consumption at the first steps of a system design. We introduce multi-level power models and show how to use them at different levels of the specification refinement in the model-based AADL (Architecture & Analysis Design Language) design flow. Those power models, with the underlying methodology for power estimation, are currently being integrated in the Open Source AADL Tool Environment (OSATE) under the name CAT: Consumption Analysis Toolbox. Its first prototype gives, in the case of a processor binding, power consumption estimations, for software components in the AADL component assembly model, with a maximal error ranging roughly from 5% at the lowest refinement level (the source code of the software component is known), to 30% at the highest level (only the operating frequency and basic target configuration parameters are considered). We illustrate our approach with the power model of a simple RISC (PowerPC 405), of a complex DSP (TI C62), and of a FPGA (from ALTERA). We show how those models can be used at different levels in the AADL flow. Obviously, the power consumption of Operating System (OS) services is also to be considered here. We show that the OS principal impact on the overall consumption is mainly due to services implying data transfers. We introduce a methodology to model Inter-Process Communications (IPC) power and energy consumption, and illustrate this methodology on the building and use of a model for Ethernet based inter-process communications.

Keywords

Power and energy consumption modelling Model driven engineering AADL Embedded system Processors FPGA 

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Eric Senn
    • 1
  • Saadia Douhib
  • Dominique Blouin
  • Johann Laurent
  • Skander Turki
  • Jean-Philippe Diguet
  1. 1.Lab-STICC, CNRS UMR 3192Université de Bretagne SudLorientFrance

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