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Run-time modeling and estimation of operating system power consumption
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Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
San Diego, CA, USA
SESSION: Operating systems table of contents
Pages: 160 - 171  
Year of Publication: 2003
ISBN:1-58113-664-1
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Authors
Tao Li  University of Texas at Austin, Austin, TX
Lizy Kurian John  University of Texas at Austin, Austin, TX
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 21,   Downloads (12 Months): 146,   Citation Count: 8
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ABSTRACT

The increasing constraints on power consumption in many computing systems point to the need for power modeling and estimation for all components of a system. The Operating System (OS) constitutes a major software component and dissipates a significant portion of total power in many modern application executions. Therefore, modeling OS power is imperative for accurate software power evaluation, as well as power management (e.g. dynamic thermal control and equal energy scheduling) in the light of OS-intensive workloads. This paper characterizes the power behavior of a commercial OS across a wide spectrum of applications to understand OS energy profiles and then proposes various models to cost-effectively estimate its run-time energy dissipation. The proposed models rely on a few simple parameters and have various degrees of complexity and accuracy. Experiments show that compared with cycle-accurate full-system simulation, the model can predict cumulative OS energy to within 1% accuracy for a set of benchmark programs evaluated on a high-end superscalar microprocessor. When applied to track run-time OS energy profiles, the proposed routine level OS power model offers superior accuracy than a simpler, flat OS power model, yielding per-routine estimation error of less than 6%. The most striking observation is the strong correlation between power consumption and the instructions per cycle (IPC) during OS routine executions. Since tools and methodology to measure IPC exist on modern microprocessors, the proposed models can estimate OS power for run-time dynamic thermal and energy management.


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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CITED BY  8

Collaborative Colleagues:
Tao Li: colleagues
Lizy Kurian John: colleagues

Peer to Peer - Readers of this Article have also read: