Skip to main content
SpringerLink
Log in

Improved utilization and responsiveness with gang scheduling

  • Conference paper
  • First Online:
Job Scheduling Strategies for Parallel Processing (JSSPP 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1291))

Included in the following conference series:

Abstract

Most commercial multicomputers use space-slicing schemes in which each scheduling decision has an unknown impact on the future: should a job be scheduled, risking that it will block other larger jobs later, or should the processors be left idle for now in anticipation of future arrivals? This dilemma is solved by using gang scheduling, because then the impact of each decision is limited to its time slice, and future arrivals can be accommodated in other time slices. This added flexibility is shown to improve overall system utilization and responsiveness. Empirical evidence from using gang scheduling on a Cray T3D installed at Lawrence Livermore National Lab corroborates these results, and shows conclusively that gang scheduling can be very effective with current technology.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. G. Alverson, S. Kahan, R. Korry, C. McCann, and B. Smith, “Scheduling on the Tera MTA”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 19–44, Springer-Verlag, 1995. Lecture Notes in Computer Science Vol. 949.

    Google Scholar 

  2. Cray Research, Inc., Cray T3D System Architecture Overview. Order number HR-04033, Sep 1993.

    Google Scholar 

  3. D. Das Sharma and D. K. Pradhan, “Job scheduling in mesh multicomputers In Intl. Conf. Parallel Processing, vol. II, pp. 251–258, Aug 1994.

    Google Scholar 

  4. D. G. Feitelson, “Packing schemes for gang scheduling”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 89–110, Springer-Verlag, 1996. Lecture Notes in Computer Science Vol. 1162.

    Google Scholar 

  5. D. G. Feitelson, A Survey of Scheduling in Multiprogrammed Parallel Systems. Research Report RC 19790 (87657), IBM T. J. Watson Research Center, Oct 1994.

    Google Scholar 

  6. D. G. Feitelson and B. Nitzberg, “Job characteristics of a production parallel scientific workload on the NASA Ames iPSC/860”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 337–360, Springer-Verlag, 1995. Lecture Notes in Computer Science Vol. 949.

    Google Scholar 

  7. D. G. Feitelson and L. Rudolph, “Distributed hierarchical control for parallel processing”. Computer 23(5), pp. 65–77, May 1990.

    Article  Google Scholar 

  8. D. G. Feitelson and L. Rudolph, “Evaluation of design choices for gang scheduling using distributed hierarchical control”. J. Parallel & Distributed Comput. 35(1), pp. 18–34, May 1996.

    Google Scholar 

  9. D. G. Feitelson and L. Rudolph, “Gang scheduling performance benefits for finegrain synchronization”. J. Parallel & Distributed Comput. 16(4), pp. 306–318, Dec 1992.

    Google Scholar 

  10. D. G. Feitelson and L. Rudolph, “Parallel job scheduling: issues and approaches”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 1–18, Springer-Verlag, 1995. Lecture Notes in Computer Science Vol. 949.

    Google Scholar 

  11. D. G. Feitelson, L. Rudolph, U. Schwiegelshohn, K. C. Sevcik, and P. Wong, “Theory and practice in parallel job scheduling”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), Springer Verlag, 1997. Lecture Notes in Computer Science (this volume).

    Google Scholar 

  12. B. Gorda and R. Wolski, “Time sharing massively parallel machines”. In Intl. Conf. Parallel Processing, vol. II, pp. 214–217, Aug 1995.

    Google Scholar 

  13. B. C. Gorda and E. D. Brooks III, Gang Scheduling a Parallel Machine. Technical Report UCRL-JC-107020, Lawrence Livermore National Laboratory, Dec 1991.

    Google Scholar 

  14. R. L. Henderson, “Job scheduling under the portable batch system” In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 279–294, Springer-Verlag, 1995. Lecture Notes in Computer Science Vola 949.

    Google Scholar 

  15. S. Hotovy, “Workload evolution on the Cornell Theory Center IBM SP2”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 27–40, Springer-Verlag, 1996. Lecture Notes in Computer Science Vol. 1162.

    Google Scholar 

  16. Intel Corp., iPSC/860 Multi-User Accounting, Control, and Scheduling Utilities Manual. Order number 312261-002, May 1992.

    Google Scholar 

  17. M. Jette, D. Storch, and E. Yim, “Timesharing the Cray T3D”. In Cray User Group, pp. 247–252, Mar 1996.

    Google Scholar 

  18. K. Li and K-H. Cheng, “A two-dimensional buddy system for dynamic resource allocation in a partitionable mesh connected system”. J. Parallel & Distributed Comput. 12(1), pp. 79–83, May 1991.

    Google Scholar 

  19. D. Lifka, “The ANL/IBM SP scheduling system”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 295-–303, Springer-Verlag, 1995. Lecture Notes in Computer Science Vol. 949.

    Google Scholar 

  20. C. McCann, R. Vaswani, and J. Zahorjan, “A dynamic processor allocation policy for multiprogrammed shared-memory multiprocessors”. ACM Trans. Comput. Syst. 11(2), pp. 146–178, May 1993.

    Article  Google Scholar 

  21. C. McCann and J. Zahorjan, “Scheduling memory constrained jobs on distributed memory parallel computers”. In SIGMETRICS Conf. Measurement & Modeling of Comput. Syst., pp. 208–219, May 1995.

    Google Scholar 

  22. J. K. Ousterhout, “Scheduling techniques for concurrent systems”. In 3rd Intl. Conf. Distributed Comput. Syst., pp. 22–30, Oct 1982.

    Google Scholar 

  23. E. W. Parsons and K. C. Sevcik, “Multiprocessor scheduling for high-variability service time distributions”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 127–145, Springer-Verlag, 1995. Lecture Notes in Computer Science Vol. 949.

    Google Scholar 

  24. R. C. Regis, “Multiserver queueing models of multiprocessing systems”. IEEE Trans. Comput. C-22(8), pp. 736–745, Aug 1973.

    Google Scholar 

  25. E. Rosti, E. Smirni, L. W. Dowdy, G. Serazzi, and B. M. Carlson, “Robust partitioning schemes of multiprocessor systems”. Performance Evaluation 19(2-3), pp. 141–165, Mar 1994.

    Article  Google Scholar 

  26. E. Rosti, E. Smirni, G. Serazzi, and L. W. Dowdy, “Analysis of non-work-conserving processor partitioning policies”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 165–181, Springer-Verlag, 1995. Lecture Notes in Computer Science Vol. 949.

    Google Scholar 

  27. B. Schnor, “Dynamic scheduling of parallel applications”. In Parallel Computing Technologies, V. Malyshkin (ed.), pp. 109–116, Springer-Verlag, Sep 1995. Lecture Notes in Computer Science vol. 964.

    Google Scholar 

  28. K. C. Sevcik, “Application scheduling and processor allocation in multiprogrammed parallel processing systems”. Performance Evaluation 19(2-3), pp. 107–140, Mar 1994.

    Article  Google Scholar 

  29. K. C. Sevcik, “Characterization of parallelism in applications and their use in scheduling”. In SIGMETRICS Conf. Measurement & Modeling of Comput. Syst., pp. 171–180, May 1989.

    Google Scholar 

  30. A. Tucker and A. Gupta, “Process control and scheduling issues for multiprogrammed shared-memory multiprocessors”. In 12th Symp. Operating Systems Principles, pp. 159–166, Dec 1989.

    Google Scholar 

  31. M. Wan, R. Moore, G. Kremenek, and K. Steube, “A batch scheduler for the Intel Paragon with a non-contiguous node allocation algorithm”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 48–64, Springer-Verlag, 1996. Lecture Notes in Computer Science Vol. 1162.

    Google Scholar 

  32. K. Windisch, V. Lo, R. Moore, D. Feitelson, and B. Nitzberg, “A comparison of workload traces from two production parallel machines”. In 6th Symp. Frontiers Massively Parallel Comput., pp. 319–326, Oct 1996.

    Google Scholar 

  33. Q. Yang and H. Wang, “A new graph approach to minimizing processor fragmentation in hypercube multiprocessors”. IEEE Trans. Parallel & Distributed Syst. 4(10), pp. 1165–1171, Oct 1993.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computer Science, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel

    Dror G. Feitelson

  2. Livermore Computing, Lawrence Livermore National Laboratory, 94550, Livermore, CA

    Morris A. Jettee

Authors
  1. Dror G. Feitelson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Morris A. Jettee
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Dror G. Feitelson Larry Rudolph

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Feitelson, D.G., Jettee, M.A. (1997). Improved utilization and responsiveness with gang scheduling. In: Feitelson, D.G., Rudolph, L. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 1997. Lecture Notes in Computer Science, vol 1291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63574-2_24

Download citation

  • DOI: https://doi.org/10.1007/3-540-63574-2_24

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63574-1

  • Online ISBN: 978-3-540-69599-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation