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SHIP: A Scalable Hierarchical Power Control Architecture for Large-Scale Data Centers

Published: 01 January 2012 Publication History

Abstract

In today's data centers, precisely controlling server power consumption is an essential way to avoid system failures caused by power capacity overload or overheating due to increasingly high server density. While various power control strategies have been recently proposed, existing solutions are not scalable to control the power consumption of an entire large-scale data center, because these solutions are designed only for a single server or a rack enclosure. In a modern data center, however, power control needs to be enforced at three levels: rack enclosure, power distribution unit, and the entire data center, due to the physical and contractual power limits at each level. This paper presents SHIP, a highly scalable hierarchical power control architecture for large-scale data centers. SHIP is designed based on well-established control theory for analytical assurance of control accuracy and system stability. Empirical results on a physical testbed show that our control solution can provide precise power control, as well as power differentiations for optimized system performance and desired server priorities. In addition, our extensive simulation results based on a real trace file demonstrate the efficacy of our control solution in large-scale data centers composed of 5,415 servers.

Cited By

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  • (2020)ThunderboltProceedings of the 14th USENIX Conference on Operating Systems Design and Implementation10.5555/3488766.3488836(1241-1255)Online publication date: 4-Nov-2020
  • (2020)Data Center Power Oversubscription with a Medium Voltage Power Plane and Priority-Aware CappingProceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3373376.3378533(497-511)Online publication date: 9-Mar-2020
  • (2019)PERQProceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing10.1145/3307681.3326607(171-182)Online publication date: 17-Jun-2019
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  1. SHIP: A Scalable Hierarchical Power Control Architecture for Large-Scale Data Centers

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      Published In

      cover image IEEE Transactions on Parallel and Distributed Systems
      IEEE Transactions on Parallel and Distributed Systems  Volume 23, Issue 1
      January 2012
      191 pages

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      IEEE Press

      Publication History

      Published: 01 January 2012

      Author Tags

      1. Power capping
      2. control theory
      3. data centers
      4. power management
      5. scalability
      6. servers.

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      Cited By

      View all
      • (2020)ThunderboltProceedings of the 14th USENIX Conference on Operating Systems Design and Implementation10.5555/3488766.3488836(1241-1255)Online publication date: 4-Nov-2020
      • (2020)Data Center Power Oversubscription with a Medium Voltage Power Plane and Priority-Aware CappingProceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3373376.3378533(497-511)Online publication date: 9-Mar-2020
      • (2019)PERQProceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing10.1145/3307681.3326607(171-182)Online publication date: 17-Jun-2019
      • (2019)Distributed strategies for computational sprintsCommunications of the ACM10.1145/329988562:2(98-106)Online publication date: 28-Jan-2019
      • (2019)A Survey on Power Management Techniques for Oversubscription of Multi-Tenant Data CentersACM Computing Surveys10.1145/329104952:1(1-31)Online publication date: 13-Feb-2019
      • (2019)A Renewable Energy Driven Approach for Computational SprintingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2018.289023030:7(1449-1463)Online publication date: 13-Jun-2019
      • (2019)Event driven power consumption optimization control model of GPU clustersCluster Computing10.1007/s10586-018-02886-x22:3(965-979)Online publication date: 1-Sep-2019
      • (2018)CapNetACM Transactions on Sensor Networks10.1145/327862415:1(1-34)Online publication date: 15-Dec-2018
      • (2017)Computational SprintingACM Transactions on Computer Systems10.1145/301442834:4(1-26)Online publication date: 9-Jan-2017
      • (2017)Hybrid Energy Storage with Supercapacitor for Cost-Efficient Data Center Power Shaving and CappingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2016.260771528:4(1105-1118)Online publication date: 1-Apr-2017
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