Skip to main content

Energy Efficiency in HPC Data Centers: Latest Advances to Build the Path to Exascale

  • Chapter
  • First Online:

Abstract

Nowadays, moderating energy consumption and building eco-friendly computing infrastructure is a major goal in large data centers. Moreover, data center energy usage has risen dramatically over the past decade and will continue to grow in-step with the High Performance Computing (HPC) intensive workloads which are at the heart of our modern life. The recent advances in the technology has driven the data center into a new phase of expansion featuring solutions with higher density. To this end, much has been done to increase server efficiency and IT space utilization. In this chapter, we will provide a state-of-the-art overview as regards energy-efficiency in High Performance Computing (HPC) facilities while describing the open challenges the research community has to face in the coming years to enable the building and usage of an Exascale platform by 2020.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    Top500 List of November 2012—see http://top500.org.

  2. 2.

    See http://www.cs.huji.ac.il/labs/parallel/workload.

  3. 3.

    http://www.tacc.utexas.edu/resources/hpc/stampede.

References

  1. AMD G-T40N. http://www.amd.com/us/products/embedded/processors/Pages/g-series.aspx.

  2. AMD Unveils Server Strategy and Roadmap. http:/www.amd.com/us/press-releases/Pages/amd-unveils-2013june18.aspx.

  3. DOE Extreme-Scale Technology Acceleration FastForward. https://asc.llnl.gov/fastforward/.

  4. European Mont-Blanc Project. http://www.montblanc-project.eu/.

  5. Grid'5000. [online] http://grid5000.fr.

  6. Iceotope Servers. http://www.iceotope.com/.

  7. Intel Atom Processor N2600. http://ark.intel.com/products/58916/intel-atom-processor-n2600-(1m-cache-1_6-ghz).

  8. Intel Core i7-3615QE. http://ark.intel.com/products/65709/Intel-Core-i7-3615QE-Processor-(6M-Cache-up-to-3_30-GHz).

  9. Intel unveils new technologies for efficient cloud datacenters. http://newsroom.intel.com/community/intel_newsroom/blog/2013/09/04/intel-unveils-new-technologies-for-efficient-cloud-datacenters.

  10. IOR HPC benchmark. [online] http://sourceforge.net/projects/ior-sio/.

  11. Iozone filesystem benchmark. [online] http://www.iozone.org/.

  12. SuperMUC - First Commercial IBM Hot-Water Cooled Supercomputer. http://www-03.ibm.com/press/us/en/pressrelease/38065.wss.

  13. The Green500 List - November 2013. http://green500.org/lists/green201311.

  14. Top500. [online] http://www.top500.org.

  15. X-Stack Software. http://www.xstack.org/.

  16. PUE (tm): A comprehensive examination of the metric. White paper, The Green Grid, 2012.

    Google Scholar 

  17. Q. Ali, V. Kiriansky, J. Simons, and P. Zaroo. Performance evaluation of HPC benchmarks on VMware’s ESXi server. In Proceedings of the 2011 international conference on Parallel Processing, Euro-Par'11, pages 213–222, Berlin, Heidelberg, 2012. Springer-Verlag.

    Google Scholar 

  18. P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho, R. Neugebauer, I. Pratt, and A. Warfield. Xen and the art of virtualization. In Proceedings of the nineteenth ACM symposium on Operating systems principles, SOSP '03, pages 164–177, New York, NY, USA, 2003. ACM.

    Google Scholar 

  19. R. Bolze, F. Cappello, E. Caron, M. Daydé, F. Desprez, E. Jeannot, Y. Jégou, S. Lanteri, J. Leduc, N. Melab, G. Mornet, R. Namyst, P. Primet, B. Quetier, O. Richard, E.-G. Talbi, and I. Touche. Grid'5000: A large scale and highly reconfigurable experimental grid testbed. Int. J. High Perform. Comput. Appl., 20(4):481–494, Nov. 2006.

    Article  Google Scholar 

  20. N. Capit and al. A batch scheduler with high level components. In Cluster computing and Grid 2005 (CCGrid05), 2005.

    Google Scholar 

  21. S. J. Chapin, W. Cirne, D. G. Feitelson, J. P. Jones, S. T. Leutenegger, U. Schwiegelshohn, W. Smith, and D. Talby. Benchmarks and standards for the evaluation of parallel job schedulers. In D. G. Feitelson and L. Rudolph, editors, JSSPP, pages 67–90. 1999. Lect. Notes Comput. Sci. vol. 1659.

    Google Scholar 

  22. D. T. D. G. Feitelson and D. Krakov. Experience with the parallel workloads archive. Technical report, School of Computer Science and Engineering, The Hebrew University of Jerusalem, 2012.

    Google Scholar 

  23. G. Da-Costa, J.-P. Gelas, Y. Georgiou, L. Lefèvre, A.-C. Orgerie, J.-M. Pierson, O. Richard, and K. Sharma. The green-net framework: Energy efficiency in large scale distributed systems. In HPPAC 2009, 2009.

    Google Scholar 

  24. J. Emeras. Workload Traces Analysis and Replay in Large Scale Distributed Systems. PhD thesis, LIG, Grenoble - France, To be defended October 1st 2013. currently available at: https://forge.imag.fr/docman/view.php/359/754/thesis_emeras_28aug13.pdf.

  25. M. Flynn. Some computer organizations and their effectiveness. IEEE Transactions on Computers, C(21):948–960, 1972.

    Google Scholar 

  26. Y. Georgiou. Contributions for Resource and Job Management in High Performance Computing. PhD thesis, LIG, Grenoble - France, Sep 2010.

    Google Scholar 

  27. M. Guzek, S. Varrette, V. Plugaru, J. E. Sanchez, and P. Bouvry. A Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment. In Proc. of the Intl. Conf. on Energy Efficiency in Large Scale Distributed Systems (EE-LSDS'13), volume 8046 of LNCS, Vienna, Austria, Apr 2013. Springer Verlag.

    Google Scholar 

  28. R. Januszewski, N. Meyer, and J. Nowicka. Evaluation of the impact of direct warm-water cooling of the HPC servers on the data center ecosystem. In To appear in International Supercomputing Conference 2014, Leipzig, Germany, 2014.

    Google Scholar 

  29. M. Jarus, S. Varette, A. Oleksiak, and P. Bouvry. Performance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors. In Energy Efficiency in Large Scale Distributed Systems, Lecture Notes in Computer Science, pages 182–200. Springer Berlin Heidelberg, 2013.

    Google Scholar 

  30. A. Kivity and al. kvm: the Linux virtual machine monitor. In Ottawa Linux Symposium, pages 225–230, July 2007.

    Google Scholar 

  31. V. Kundra. Federal data center consolidation initiative. Memorandum for chief information officers, Office of Management and Budget of the USA, 2010.

    Google Scholar 

  32. E. Le Seur and G. Heiser. Dynamic voltage and frequency scaling: the laws of diminishing returns. In HotPower'10 Proceedings of the 2010 international conference on Power aware computing and systems, California, USA, 2010. USENIX Association Berkeley.

    Google Scholar 

  33. R. C. Murphy, K. B. Wheeler, B. W. Barrett, and J. A. Ang. Introducing the graph 500. In Cray User Group, 2010.

    Google Scholar 

  34. A.-C. Orgerie, L. Lefèvre, and J.-P. Gelas. Save watts in your grid: Green strategies for energy-aware framework in large scale distributed systems. In 14th IEEE International Conference on Parallel and Distributed Systems (ICPADS), Melbourne, Australia, Dec. 2008.

    Google Scholar 

  35. A. Petitet, C. Whaley, J. Dongarra, A. Cleary, and P. Luszczek. HPL - A Portable Implementation of the High-Performance Linpack Benchmark for Distributed-Memory Computers.

    Google Scholar 

  36. N. Rasmussen. Air Distribution Architecture Options for Mission Critical Facilities Whitepaper #55. Technical report, American Power Conversion, 2003.

    Google Scholar 

  37. S. Sharma, C.-H. Hsu, and W. chun Feng. Making a case for a Green500 list. In Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International, pages 8 pp.–, 2006.

    Google Scholar 

  38. S. Varrette, M. Guzek, V. Plugaru, X. Besseron, and P. Bouvry. HPC Performance and Energy-Efficiency of Xen, KVM and VMware Hypervisors. In Proc. of the 25th Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2013), Porto de Galinhas, Brazil, Oct. 2013. IEEE Computer Society.

    Google Scholar 

  39. M. vor dem Berge, J. Buchholz, L. Cupertino, G. Da Costa, A. Donoghue, G. Gallizo, M. Jarus, L. Lopez, A. Oleksiak, E. Pages, W. Piatek, J.-M. Pierson, T. Piontek, D. Rathgeb, J. Salom, L. Siso, E. Volk, W. U., and T. Zilio. CoolEmAll: Models and Tools for Planning and Operating Energy Efficient Data Centres. To appear in: Samee Khan, Albert Zomaya (eds.) Handbook on Data Centers.

    Google Scholar 

  40. M. vor dem Berge, G. Da Costa, A. Kopecki, A. Oleksiak, J.-M. Pierson, T. Piontek, E. Volk, and S. Wesner. Modeling and Simulation of Data Center Energy-Efficiency in CoolEmAll. Energy Efficient Data Centers. Lecture Notes in Computer Science, 7396:25–36, 2012.

    Google Scholar 

Download references

Acknowledgments

The research presented in this paper is partially funded by a grant from Polish National Science Center under award number 2013/08/A/ST6/00296.

The experiments presented in this paper were carried out using the HPC facility of the University of Luxembourg and Poznan Supercomputing and Networking Center.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sébastien Varrette .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this chapter

Cite this chapter

Varrette, S., Bouvry, P., Jarus, M., Oleksiak, A. (2015). Energy Efficiency in HPC Data Centers: Latest Advances to Build the Path to Exascale. In: Khan, S., Zomaya, A. (eds) Handbook on Data Centers. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2092-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2092-1_3

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4939-2091-4

  • Online ISBN: 978-1-4939-2092-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics