Skip to main content

Advertisement

Springer Nature Link
Log in

Performance scalability and energy consumption on distributed and many-core platforms

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

In this paper, the performance evaluation of distributed and many-core computer complexes, in conjunction with their consumed energy, is investigated. The distributed execution of a specific problem on an interconnected processors platform requires a larger amount of energy compared to the sequential execution. The primary reason is the inability to fully parallelize a problem due to the unavoidable serial parts and the intercommunication of utilized processors. Distributed and many-core platforms are evaluated for the power their processors demand at the idle and fully utilized state. In proportion to the parallelized percentage each time, the estimations of the theoretical model were compared to the experimental results achieved on the basis of the performance/power and performance/energy ratio metrics. Analytical formulas for evaluating the experimental energy consumption have been developed for both platforms, while the experimental vehicle was a widely known algorithm with different parallelization percentages.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Amdahl G (1967) Validity of the single-processor approach to achieving large scale computing capabilities. In: Proceedings of the AFIPS conference

  2. Mudge T (2001) Power: a first-class architectural design constraint. Computer 52–58

  3. Benner RE, Gustafson JL, Montry GR (1988) Development and analysis of scientific application programs on a 1024-processor hypercube. In: SAND 88–0317, Sandia National Laboratories

  4. Shi Y (1996) Reevaluating Amdahl’s law and Gustafson’s law. Computer and Information Sciences Department, Temple University

  5. Woo DH, Lee HHS (2008) Extending Amdahl’s law for Energy-efficient computing in the many-core era. IEEE Comput 41(12):24–31

    Article  Google Scholar 

  6. Gustafson JL (1988) Reevaluating Amdahl’s law. CACM 31(5):532–533

    Article  Google Scholar 

  7. Gonzalez R, Horowitz M (1996) Energy dissipation in general-purpose microprocessors. IEEE J Solid State Circuits 31(9):1277–1284

    Article  Google Scholar 

  8. Lu J, Guo Y (2011) Energy-aware fixed-priority multi-core scheduling for real-time systems. In: Proceedings of the RTCSA-IEEE 17th international conference, vol 1, pp 277–281

  9. Yang L, Lin M, Yang T (2012) Multi-core fixed priority DVS scheduling. In: Algorithms and architectures for parallel processing, Lecture Notes in Computer Science, vol 7439, pp 517–530

  10. High-Performance Portable MPI (MPICH) Last visit: Apr 2014. http://www.mpich.org

  11. AMD Server Processors Last visit: Apr 2014. http://www.amd.com/en-us/products/server

  12. Londono SM, Gyvez JP (2010) Extending Amdahl’s law for energy efficiency. In: Proceedings of the ICEAC conference, pp 1–4

  13. Marowka A (2012) Extending Amdahl’s law for heterogeneous computing. In: Proceedings of the IEEE ISPA conference, pp 309–316

  14. Cassidy AS, Andreou AG (2012) Beyond Amdahl’s law: an objective function that links multiprocessor performance gains to delay and energy. IEEE Trans Comput 61(8):1110–1126

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 , Xanthi, Greece

    E. M. Karanikolaou & M. P. Bekakos

  2. Faculty of Electronic Engineering, A. Medvedeva 14, P.O. Box 73, 18000 , Nis, Serbia

    E. I. Milovanović & I. Ž. Milovanović

Authors
  1. E. M. Karanikolaou
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. E. I. Milovanović
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. I. Ž. Milovanović
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. M. P. Bekakos
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to E. M. Karanikolaou.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Karanikolaou, E.M., Milovanović, E.I., Milovanović, I.Ž. et al. Performance scalability and energy consumption on distributed and many-core platforms. J Supercomput 70, 349–364 (2014). https://doi.org/10.1007/s11227-014-1248-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-014-1248-0

Keywords