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Link to original content: https://link.springer.com/doi/10.1007/978-3-540-73625-7_10
Trade-Offs Between Voltage Scaling and Processor Shutdown for Low-Energy Embedded Multiprocessors | SpringerLink
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Trade-Offs Between Voltage Scaling and Processor Shutdown for Low-Energy Embedded Multiprocessors

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Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4599))

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Abstract

When peak performance is unnecessary, Dynamic Voltage Scaling (DVS) can be used to reduce the dynamic power consumption of embedded multiprocessors. In future technologies, however, static power consumption is expected to increase significantly. Then it will be more effective to limit the number of employed processors, and use a combination of DVS and processor shutdown. Scheduling heuristics are presented that determine the best trade-off between these three techniques: DVS, processor shutdown, and finding the optimal number of processors. Experimental results show that our approach reduces the total energy consumption by up to 25% for tight deadlines and by up to 57% for loose deadlines compared to DVS. We also compare the energy consumed by our scheduling algorithm to two lower bounds, and show that our best approach leaves little room for improvement.

This research was supported in part by the Netherlands Organisation for Scientific Research (NWO).

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Stamatis Vassiliadis Mladen Bereković Timo D. Hämäläinen

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© 2007 Springer-Verlag Berlin Heidelberg

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de Langen, P., Juurlink, B. (2007). Trade-Offs Between Voltage Scaling and Processor Shutdown for Low-Energy Embedded Multiprocessors. In: Vassiliadis, S., Bereković, M., Hämäläinen, T.D. (eds) Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2007. Lecture Notes in Computer Science, vol 4599. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73625-7_10

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  • DOI: https://doi.org/10.1007/978-3-540-73625-7_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73622-6

  • Online ISBN: 978-3-540-73625-7

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