Advertisement

On the Energy-Performance Tradeoff for Parallel Applications

  • Shikharesh Majumdar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6342)

Abstract

Improving software performance by deploying parallel software on multiple processors often comes at the cost of increasing energy consumption. This paper focuses on such energy-performance tradeoffs. Techniques for computing bounds on software speedup and energy factor that captures the energy cost are presented. Numeric examples for the bounding techniques lead to valuable insights regarding system behaviour, energy and performance.

Keywords

Amdahl’s Law Software Parallelism Speedup Average Parallelism Speedup Bounds 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Amdahl, G.: Validity of the Single Processor Approach to Achieving Large-Scale Computing Capabilities. In: AFIPS Joint Computer Conference, pp. 483–485. ACM, New York (1967)Google Scholar
  2. 2.
    Eager, D.L., Zahorjan, J., Lazowska, E.D.: Speedup versus Efficiency in Parallel Systems. IEEE Transactions on Computers 38(3), 408–423 (1989)CrossRefGoogle Scholar
  3. 3.
    Feng, W.C., Cameron, K.W.: The Green500 List: Encouraging Sustainable Supercomputing. IEEE Computer 40(12), 50–56 (2007)CrossRefGoogle Scholar
  4. 4.
    Feng, W.-C., Feng, X., Ge, R.: Supercomputing Comes of Age. IT Professional 10(1), 17–23 (2008)CrossRefGoogle Scholar
  5. 5.
    Goth, G.: The Net’s Going Green Multipronged Approach Might Save Costs, Energy — and the Climate. IEEE Internet Computing 12(1), 7–9 (2008)CrossRefGoogle Scholar
  6. 6.
    Grier, D.A.: Click Here to Empty Trash. IEEE Computer 41(9), 1–8 (2008)CrossRefGoogle Scholar
  7. 7.
    Hill, M.D., Marty, M.R.: Amdahl’s Law in the Multicore Era. IEEE Computer 41(7), 33–38 (2008)CrossRefGoogle Scholar
  8. 8.
    Hu, L., Jin, H., Liao, X., Xiong, X., Liu, H.: Magnet: A Novel Scheduling Policy for Power Reduction in Cluster with Virtual Machines. In: 2008 International Conference on Cluster Computing, pp. 13–22. IEEE Press, New York (2008)Google Scholar
  9. 9.
    Lange, K.-D.: Identifying Shades of Green: The SPECpower Benchmarks. IEEE Computer 42(3), 95–97 (2009)CrossRefGoogle Scholar
  10. 10.
    Marinescu, D.C., Morrison, J.P., Yu, C., Norvik, C., Siegel, H.J.: A Self-Organization Model for Complex Computing and Communication Systems. In: Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, pp. 149–158. IEEE Press, New York (2008)CrossRefGoogle Scholar
  11. 11.
    Murugesan, S.: Harnessing Green IT: Principles and Practices. IT Professional 10(1), 24–33 (2008)CrossRefGoogle Scholar
  12. 12.
    Niyato, D., Chaisiri, S., Sung, L.B.: Optimal Power Management for Server Farm to Support Green Computing. In: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 84–91. IEEE Press, New York (2009)Google Scholar
  13. 13.
    Orgerie, A.-C., Laurent, L., Gelas, J.-P.: 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, pp. 171–178. IEEE Press, New York (2008)Google Scholar
  14. 14.
    Riviore, S., Shah, M.A., Ranganathan, P., Kozyrakis, C., Meza, J.: Models and Metrics to Enable Energy-Efficiency Optimizations. IEEE Computer 40(12), 39–48 (2007)CrossRefGoogle Scholar
  15. 15.
    Sevcik, K.C.: Characterizations of parallelism in applications and their use in scheduling. In: 1989 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, pp. 171–180. ACM, New York (1989)CrossRefGoogle Scholar
  16. 16.
    Wang, D.A.: Meeting Green Computing Challenges. In: 10th Electronics Packaging Technology Conference, pp. 121–126. IEEE Press, New York (2008)Google Scholar
  17. 17.
    Willbanks, L.: Green: My favorite Color. IT-Professional 10(6), 64–65 (2008)CrossRefGoogle Scholar
  18. 18.
    Williams, J., Curtis, I.: Green IT: the New Computing Coat of Arms? IT-Professional 10(1), 12–16 (2008)CrossRefGoogle Scholar
  19. 19.
    Xian, C., Lu, Y.-H., Li, Z.: Energy-Aware Scheduling for Real-Time Multiprocessor Systems with Uncertain Task Execution Time. In: 44th Annual Design Automation Conference, pp. 664–669. ACM, New York (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Shikharesh Majumdar
    • 1
  1. 1.Dept. of Systems and Computer Eng.Carleton UniversityOttawaCanada

Personalised recommendations