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Performance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors

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Energy Efficiency in Large Scale Distributed Systems (EE-LSDS 2013)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8046))

Abstract

Due to growth of energy consumption by HPC servers and data centers many research efforts aim at addressing the problem of energy efficiency. Hence, the use of low power processors such as Intel Atom and ARM Cortex have recently gained more interest. In this article, we compare performance and energy efficiency of cutting-edge high-density HPC platform enclosures featuring either very high-performing processors (such as Intel Core i7 or E7) yet having low power-efficiency, or the reverse i.e. energy efficient processors (such as Intel Atom, AMD Fusion or ARM Cortex A9) yet with limited computing capacity. Our objective was to quantify in a very pragmatic way these general purpose CPUs using a set of reference benchmarks and applications run in an HPC environment, the trade-off that could exist between computing and power efficiency.

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Notes

  1. 1.

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

  2. 2.

    For licensing reasons, it was not possible to use Intel compiler on PSCN’s platforms.

References

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

  2. Energy-conscious 3D Server-on-Chip for Green Cloud. http://www.eurocloudserver.com/

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

  4. Intel Advanced Vector Extensions. http://software.intel.com/en-us/avx

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

  6. Intel Hyper-Threading. http://www.intel.com/content/www/us/en/architecture-and-technology/turbo-boost/turbo-boost-technology.html

  7. Intel SpeedStep Technology. http://www.intel.com/cd/channel/reseller/asmo-na/eng/203838.htm

  8. Intel Turbo Boost Technology. http://www.intel.com/content/www/us/en/architecture-and-technology/turbo-boost/turbo-boost-technology.html

  9. Neon Media Processing Engine. http://infocenter.arm.com/help/index.jsp?topic=/com.arm.doc.ddi0409i/index.html

  10. PandaBoard. http://pandaboard.org/

  11. Phoronix Test Suite. http://www.phoronix-test-suite.com

  12. Raspberry Pi. http://www.raspberrypi.org/

  13. Thumb 2 Technology. http://infocenter.arm.com/help/index.jsp?topic=/com.arm.doc.dui0471c/CHDFEDDB.html

  14. Basmadjian, R., Ali, N., Niedermeier, F., de Meer, H., Giuliani, G.: A methodology to predict the power consumption of servers in data centres. ACM, New York (2011)

    Google Scholar 

  15. Basmadjian, R., de Meer, H.: Evaluating and modeling power consumption of multi-core processors. In: Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet, e-Energy ’12, pp. 12:1–12:10. ACM, New York (2012)

    Google Scholar 

  16. Hoffman, K., Hedge, P.: ARM Cortex-A8 vs. Intel atom: architectural and Benchmark comparisons. Technical report, University of Texas at Dallas (2009)

    Google Scholar 

  17. Jarus, M., Oleksiak, A., Piontek, T., Weglarz, J.: Runtime power usage estimation of HPC servers for various classes of real-life applications. To appear in Future Generation Computer Systems (2013)

    Google Scholar 

  18. Ou, Z., Pang, B., Deng, Y., Nurminen, J., Ylä-Jääski, A., Hui, P.: Energy- and cost-efficiency analysis of ARM-based clusters. In: 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012, pp. 115–123 (2012)

    Google Scholar 

  19. Padoin, E.L., de Oliveira, D., Velho, P., Navaux, P.: Time-to-solution and energy-to-solution: a comparison between ARM and Xeon. In: Third Workshop on Applications for Multi-Core Architectures (WAMCA), pp. 48–53 (2012)

    Google Scholar 

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Acknowledgments

The experiments presented in this paper were carried out using the HPC facility of the University of Luxembourg and Poznan Supercomputing and Networking Center. The research presented in this paper was partially supported by a grant from Polish National Science Center (under award number 636/N-COST/09/2010/0), the FNR INTER-CNRS-11-03 Green@cloud project and the COST action IC0804.

Author information

Authors and Affiliations

  1. Poznań Supercomputing and Networking Center, Noskowskiego 10, Poznań, Poland

    Mateusz Jarus & Ariel Oleksiak

  2. Computer Science and Communication (CSC) Research Unit, University of Luxembourg, 6, rue Richard Coudenhove-Kalergi, 1359 , Luxembourg, Luxembourg

    Sébastien Varrette & Pascal Bouvry

Authors
  1. Mateusz Jarus
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  2. Sébastien Varrette
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  3. Ariel Oleksiak
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  4. Pascal Bouvry
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Corresponding author

Correspondence to Mateusz Jarus .

Editor information

Editors and Affiliations

  1. Toulouse University, Toulouse, France

    Jean-Marc Pierson

  2. Toulouse University, Toulouse, France

    Georges Da Costa

  3. Technical University of Denmark, Lyngby, Denmark

    Lars Dittmann

A    Appendix: HPL Runs Details

A    Appendix: HPL Runs Details

See Figs. 8 and 9.

Fig. 8.
figure 8figure 8

HPLinpack 2.1 – Single CPU benchmark. Computing performances (left) and power consumption of the best runs (right) on the considered platforms.

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Fig. 9.
figure 9

HPLinpack 2.1 – Energy profile when performing the complete platforms benchmark.

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Jarus, M., Varrette, S., Oleksiak, A., Bouvry, P. (2013). Performance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors. In: Pierson, JM., Da Costa, G., Dittmann, L. (eds) Energy Efficiency in Large Scale Distributed Systems. EE-LSDS 2013. Lecture Notes in Computer Science(), vol 8046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40517-4_16

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  • DOI: https://doi.org/10.1007/978-3-642-40517-4_16

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  • Print ISBN: 978-3-642-40516-7

  • Online ISBN: 978-3-642-40517-4

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