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Energy-efficient policies for embedded clusters
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Volume 40 ,  Issue 7  (July 2005) table of contents
Proceedings of the 2005 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
SESSION: Distributed computing table of contents
Pages: 1 - 10  
Year of Publication: 2005
ISSN:0362-1340
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Authors
Ruibin Xu  University of Pittsburgh, Pittsburgh, PA
Dakai Zhu  University of Pittsburgh, Pittsburgh, PA
Cosmin Rusu  University of Pittsburgh, Pittsburgh, PA
Rami Melhem  University of Pittsburgh, Pittsburgh, PA
Daniel Mossé  University of Pittsburgh, Pittsburgh, PA
Publisher
ACM  New York, NY, USA
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ABSTRACT

Power conservation has become a key design issue for many systems, including clusters deployed for embedded systems, where power availability ultimately determines system lifetime. These clusters execute a high rate of requests of highly-variable length, such as in satellite-based multiprocessor systems. The goal of power management in such systems is to minimize the aggregate energy consumption of the whole cluster while ensuring timely responses to requests. In the past, dynamic voltage scaling (DVS) and on/off schemes have been studied under the assumptions of continuously tunable processor frequencies and perfect load-balancing. In this work, we focus on the more realistic case of discrete processor frequencies and propose a new policy that adjusts the number of active nodes based on the system load, not system frequency. We also design a threshold scheme which prevents the system from reacting to short-lived temporary workload changes in the presence of unstable incoming workload. Simulation and implementation results on real hardware show that our policy is very effective in reducing the overall power consumption of clusters executing embedded applications.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Ruibin Xu: colleagues
Dakai Zhu: colleagues
Cosmin Rusu: colleagues
Rami Melhem: colleagues
Daniel Mossé: colleagues