Skip to main content
SpringerLink
Log in

Scalably Scheduling Power-Heterogeneous Processors

  • Conference paper
Automata, Languages and Programming (ICALP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6198))

Included in the following conference series:

Abstract

We show that a natural online algorithm for scheduling jobs on a heterogeneous multiprocessor, with arbitrary power functions, is scalable for the objective function of weighted flow plus energy.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albers, S., Fujiwara, H.: Energy-efficient algorithms for flow time minimization. ACM Transactions on Algorithms 3(4) (2007)

    Google Scholar 

  2. Andrew, L.L., Wierman, A., Tang, A.: Optimal speed scaling under arbitrary power functions. SIGMETRICS Performance Evaluation Review 37(2), 39–41 (2009)

    Article  Google Scholar 

  3. Bansal, N., Chan, H.L.: Weighted flow time does not admit o(1)-competitive algorithms. In: SODA, pp. 1238–1244 (2009)

    Google Scholar 

  4. Bansal, N., Chan, H.L., Lam, T.W., Lee, L.K.: Scheduling for speed bounded processors. In: Aceto, L., Damgård, I., Goldberg, L.A., Halldórsson, M.M., Ingólfsdóttir, A., Walukiewicz, I. (eds.) ICALP 2008, Part I. LNCS, vol. 5125, pp. 409–420. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  5. Bansal, N., Chan, H.L., Pruhs, K.: Speed scaling with an arbitrary power function. In: SODA, pp. 693–701 (2009)

    Google Scholar 

  6. Bansal, N., Pruhs, K., Stein, C.: Speed scaling for weighted flow time. SIAM Journal on Computing 39(4) (2009)

    Google Scholar 

  7. Becchetti, L., Leonardi, S., Marchetti-Spaccamela, A., Pruhs, K.: Online weighted flow time and deadline scheduling. J. Discrete Algorithms 4(3), 339–352 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  8. Bower, F.A., Sorin, D.J., Cox, L.P.: The impact of dynamically heterogeneous multicore processors on thread scheduling. IEEE Micro 28(3), 17–25 (2008)

    Article  Google Scholar 

  9. Chadha, J.S., Garg, N., Kumar, A., Muralidhara, V.N.: A competitive algorithm for minimizing weighted flow time on unrelatedmachines with speed augmentation. In: STOC, pp. 679–684 (2009)

    Google Scholar 

  10. Chan, H.L., Edmonds, J., Lam, T.W., Lee, L.K., Marchetti-Spaccamela, A., Pruhs, K.: Nonclairvoyant speed scaling for flow and energy. In: STACS, pp. 255–264 (2009)

    Google Scholar 

  11. Greiner, G., Nonner, T., Souza, A.: The bell is ringing in speed-scaled multiprocessor scheduling. In: SPAA 2009: Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures, pp. 11–18. ACM, New York (2009)

    Chapter  Google Scholar 

  12. Kumar, R., Tullsen, D.M., Jouppi, N.P.: Core architecture optimization for heterogeneous chip multiprocessors. In: International conference on parallel architectures and compilation techniques, pp. 23–32. ACM, New York (2006)

    Google Scholar 

  13. Kumar, R., Tullsen, D.M., Ranganathan, P., Jouppi, N.P., Farkas, K.I.: Single-isa heterogeneous multi-core architectures for multithreaded workload performance. SIGARCH Computer Architecture News 32(2), 64 (2004)

    Article  Google Scholar 

  14. Lam, T.W., Lee, L.K., To, I.K.K., Wong, P.W.H.: Competitive non-migratory scheduling for flow time and energy. In: SPAA, pp. 256–264 (2008)

    Google Scholar 

  15. Lam, T.W., Lee, L.K., To, I.K.K., Wong, P.W.H.: Speed scaling functions for flow time scheduling based on active job count. In: European Symposium on Algorithms, pp. 647–659 (2008)

    Google Scholar 

  16. Leonardi, S., Raz, D.: Approximating total flow time on parallel machines. Journal of Computer and Systems Sciences 73(6), 875–891 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  17. Merritt, R.: CPU designers debate multi-core future. EE Times (February 2008)

    Google Scholar 

  18. Morad, T.Y., Weiser, U.C., Kolodny, A., Valero, M., Ayguade, E.: Performance, power efficiency and scalability of asymmetric cluster chip multiprocessors. IEEE Computer Architecture Letters 5(1), 4 (2006)

    Article  Google Scholar 

  19. Pruhs, K.: Competitive online scheduling for server systems. SIGMETRICS Performance Evaluation Review 34(4), 52–58 (2007)

    Article  Google Scholar 

  20. Pruhs, K., Sgall, J., Torng, E.: Online scheduling. In: Handbook on Scheduling, CRC Press, Boca Raton (2004)

    Google Scholar 

  21. Pruhs, K., Uthaisombut, P., Woeginger, G.J.: Getting the best response for your erg. ACM Transactions on Algorithms 4(3) (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Dept., Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Anupam Gupta & Ravishankar Krishnaswamy

  2. Computer Science Dept., University of Pittsburgh, Pittsburgh, PA, 15260, USA

    Kirk Pruhs

Authors
  1. Anupam Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ravishankar Krishnaswamy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kirk Pruhs
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Oxford University Computing Laboratory, Wolfson Building, Parks Road, OX1 3QD, Oxford, UK

    Samson Abramsky

  2. Université de Bordeaux (LaBRI) & INRIA, 351, cours de la Libération, 33405, Talence Cedex, France

    Cyril Gavoille

  3. INRIA, Centre de Recherche Bordeaux – Sud-Ouest, 351 cours de la Libération, 33405, Talence Cedex, France

    Claude Kirchner

  4. Heinz Nixdorf Institute, University of Paderborn, Fürstenallee 11, 33102, Paderborn, Germany

    Friedhelm Meyer auf der Heide

  5. University of Patras and RACTI, 26500, Patras, Greece

    Paul G. Spirakis

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gupta, A., Krishnaswamy, R., Pruhs, K. (2010). Scalably Scheduling Power-Heterogeneous Processors. In: Abramsky, S., Gavoille, C., Kirchner, C., Meyer auf der Heide, F., Spirakis, P.G. (eds) Automata, Languages and Programming. ICALP 2010. Lecture Notes in Computer Science, vol 6198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14165-2_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14165-2_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14164-5

  • Online ISBN: 978-3-642-14165-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation