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Power-Thermal Modeling and Control of Energy-Efficient Servers and Datacenters

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Handbook on Data Centers

Abstract

This continuous growth in demand for computing has resulted in larger collections of servers machines, referred to as clusters or server farms, being hosted in denser datacenters thus having a higher computational and storage capability per occupied unit volume.

J. Kim was also affiliated with ESL-EPFL during the period this research was developed.

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Notes

  1. 1.

    The scaling theory he and his colleagues formulated in 1974 postulated that MOSFETs continue to function as voltage-controlled switches while all key figures of merit (such as layout density, operating speed, and energy efficiency improve provided geometric dimensions, voltages, and doping concentrations) are consistently scaled to maintain the same electric field. This property underlies the achievement of Moore’s Law and the evolution of microelectronics over the last few decades.

  2. 2.

    A rack unit, U or RU, is a unit of measure to describe the height of rack-mount servers placed in 19-in. or a 23-in. rack, where 1U corresponds to 1.75 in. (44.45 mm) high.

  3. 3.

    In order to reduce the solution complexity, we find the solution assuming that the ideal VM consolidation. The approach is optimistic in that the estimated power consumption is lower than actual scenario due to the fragmentation of the server utilization caused by different utilizations among VMs and fractional ratio of the obtained server utilization to VM utilization in actual scenario.

  4. 4.

    In this work, we target the SLA violation to be less than 5 %. Thus, we used 95th-percentile value instead of the maximum value to characterize the worst-case behavior of the corresponding period. Considering the correlation among VMs, we can use lower percentile values, e.g., 90-, 80-th percentile, etc., to reduce more power consumption while satisfying SLA requirement, as presented in [51]. Our optimization approach is directly applicable to these cases as well.

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Acknowledgment

This work has been partially supported by the Nano-Tera.ch TRANSCEND Strategic Action, the PMSM: CT Monitoring research grant for ESL-EPFL funded by Credit Suisse AG, an ERO Research Grant Donation from Oracle for ESL-EPFL, and the EC FP7 GreenDataNet STREP project (agreement No. 609000).

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  1. DMC Research Center, Samsung Electronics, Suwon, Republic of Korea

    Jungsoo Kim

  2. Embedded Systems Laboratory, EPFL, Lausanne, Switzerland

    Mohamed M. Sabry, Martino Ruggiero & David Atienza

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  1. Jungsoo Kim
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Correspondence to Jungsoo Kim .

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  1. Department of Electrical and Computer Engineering, North Dakota State University, Fargo, North Dakota, USA

    Samee U. Khan

  2. School of Information Technologies, The University of Sydney, Sydney, New South Wales, Australia

    Albert Y. Zomaya

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Kim, J., Sabry, M., Ruggiero, M., Atienza, D. (2015). Power-Thermal Modeling and Control of Energy-Efficient Servers and Datacenters. In: Khan, S., Zomaya, A. (eds) Handbook on Data Centers. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2092-1_29

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