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Assertive Dynamic Power Management (AsDPM) Strategy for Globally Scheduled RT Multiprocessor Systems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5953))

Abstract

Emerging trends in applications with the requirement of considerable computational performance and decreasing time-to-market have urged the need of multiprocessor systems. With the increase in number of processors, there is an increased demand to efficiently control the energy and power budget of such embedded systems. Dynamic Power Management (DPM) strategies attempt to control this budget by actively changing the power consumption profile of the system. This paper presents a novel DPM strategy for real time applications. It is based on the extraction of inherently present idleness in application’s behavior to make appropriate decisions for state-transition of processors in a multiprocessor system. Experimental results show that conventional DPM approaches often yield suboptimal, if not incorrect, performance in the presence of real time constraints. Our strategy gives better energy consumption performance under the same constraints by 10.40%. Also, it reduces the number of overall state transitions by 74.85% and 59.76% for EDF and LLF scheduling policies respectively.

This work is supported by project PHERMA bearing reference ANR-06-ARFU06-003.

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© 2010 Springer-Verlag Berlin Heidelberg

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Bhatti, M.K., Farooq, M., Belleudy, C., Auguin, M., Mbarek, O. (2010). Assertive Dynamic Power Management (AsDPM) Strategy for Globally Scheduled RT Multiprocessor Systems. In: Monteiro, J., van Leuken, R. (eds) Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation. PATMOS 2009. Lecture Notes in Computer Science, vol 5953. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11802-9_16

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  • DOI: https://doi.org/10.1007/978-3-642-11802-9_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11801-2

  • Online ISBN: 978-3-642-11802-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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