Cluster Computing

, Volume 11, Issue 2, pp 183–195 | Cite as

Power capping: a prelude to power shifting

  • Charles LefurgyEmail author
  • Xiaorui Wang
  • Malcolm Ware


We present a technique that controls the peak power consumption of a high-density server by implementing a feedback controller that uses precise, system-level power measurement to periodically select the highest performance state while keeping the system within a fixed power constraint. A control theoretic methodology is applied to systematically design this control loop with analytic assurances of system stability and controller performance, despite unpredictable workloads and running environments. In a real server we are able to control power over a 1 second period to within 1 W and over an 8 second period to within 0.1 W.

Conventional servers respond to power supply constraint situations by using simple open-loop policies to set a safe performance level in order to limit peak power consumption. We show that closed-loop control can provide higher performance under these conditions and implement this technique on an IBM BladeCenter HS20 server. Experimental results demonstrate that closed-loop control provides up to 82% higher application performance compared to open-loop control and up to 17% higher performance compared to a widely used ad-hoc technique.


Power capping Power shifting Power management Power budget Feedback control Servers Power supplies Provisioning 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Lefurgy, C., et al.: Energy management for commercial servers. Computer 36(12) (2004) Google Scholar
  2. 2.
    Bohrer, P., et al.: The case for power management in web servers. In: Graybill, R., Melhem, R. (eds.) Power Aware Computing. Kluwer, Dordrecht (2002) Google Scholar
  3. 3.
    Zeng, H., et al.: Ecosystem: managing energy as a first class operating system resource. In: Int. Conf. on Architectural Support for Programming Languages and Operating Systems (2002) Google Scholar
  4. 4.
    Lu, Y.H., et al.: Operating-system directed power reduction. In: Int. Symp. on Low Power Electronics and Design (2000) Google Scholar
  5. 5.
    Hellerstein, J., et al.: Feedback Control of Computing Systems. Wiley, New York (2004) Google Scholar
  6. 6.
    Skadron, K., et al.: Control-theoretic techniques and thermal-RC modeling for accurate and localized dynamic thermal management. In: Proceedings of the Eighth International Symp. on High-Performance Computer Architecture (2002) Google Scholar
  7. 7.
    Wu, Q., et al.: Formal control techniques for power-performance management. IEEE Micro 25(5), 52–62 (2005) CrossRefGoogle Scholar
  8. 8.
    Minerick, R.J., Freeh, V.W., Kogge, P.M.: Dynamic power management using feedback. In: Proceedings of Workshop on Compilers and Operating Systems for Low Power (COLP) (2002) Google Scholar
  9. 9.
    Femal, M.E., Freeh, V.W.: Boosting data center performance through non-uniform power allocation. In: Proceedings of 2nd Intl. Conf. on Autonomic Computing (2005) Google Scholar
  10. 10.
    Sharma, V., et al.: Power-aware QoS management on web servers. In: Proceedings of the 24th International Real-Time Systems Symposium (RTSS), December 2003 Google Scholar
  11. 11.
    Chen, Y., et al.: Managing server energy and operational costs in hosting centers. In: Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, June 2005 Google Scholar
  12. 12.
    Franklin, G.F., et al.: Digital Control of Dynamic Systems, 3rd edn. Addison-Wesley, Reading (1997) Google Scholar
  13. 13.
    Intel: Maximum Power Program User Guide Version 2.0 for Nocona/Irwindale Processor (2004) Google Scholar
  14. 14.
    Brey, T., et al.: BladeCenter chassis management. IBM J. Res. Dev. 49(6) (2005) Google Scholar
  15. 15.
    Wang, X., Lefurgy, C., Ware, M.: Managing peak system-level power with feedback control. IBM Research Technical Report RC23835 (2005) Google Scholar
  16. 16.
    Norsworthy, S., Schreier, R., Temes, G. (eds.): Delta-Sigma Data Converters: Theory, Design, and Simulation. Wiley-IEEE Press, New York (1996) Google Scholar
  17. 17.
    Brooks, D., Martonosi, M.: Dynamic thermal management for high-performance microprocessors. In: Proceedings of the 7th Symp. on High Performance Computer Architecture (HPCA-7) (2001) Google Scholar
  18. 18.
    Felter, W., et al.: A performance-conserving approach for reducing peak power consumption in server systems. In: Proceedings of the International Conf. on Supercomputing (2005) Google Scholar
  19. 19.
    Poirier, C., et al.: Power and temperature control on a 90 nm itanium-family processor. In: Proceedings of Intl. Solid State Circuits Conf. (2005) Google Scholar
  20. 20.
    IBM Systems: IBM PowerExecutive 1.10 Installation and User’s Guide Version 1.10, 2nd edn. (2006) Google Scholar
  21. 21.
    Intel: Dual-Core Intel Xeon Processor 5100 Series Thermal/Mechanical Design Guide (2006) Google Scholar
  22. 22.
    Colwell, B.: We may need a new box. Computer, March (2004) Google Scholar
  23. 23.
    Ranganathan, P., et al.: Ensemble-level power management for dense blade servers. In: Proceedings of the 33rd Annual Intl. Symp. on Computer Architecture (ISCA) (2006) Google Scholar
  24. 24.
    Lefurgy, C., Wang, X., Ware, M.: Server-level power control. In: 4th IEEE Conference on Autonomic Computing (2007) Google Scholar
  25. 25.
    Fan, X., Weber, W., Barroso, L.: Power provisioning for a warehouse-sized computer. In: Proceedings of the 34th Annual Intl. Symp. on Computer Architecture (ISCA) (2007) Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Austin Research LaboratoryIBM Research DivisionAustinUSA
  2. 2.University of TennesseeKnoxvilleUSA

Personalised recommendations