Skip to main content

Selective Reservation Strategies for Backfill Job Scheduling

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2537))

Abstract

Although there is wide agreement that backfilling produces significant benefits in scheduling of parallel jobs, there is no clear consensus on which backfilling strategy is preferable - should conservative backfilling be used or the more aggressive EASY backfilling scheme. Using trace-based simulation, we show that if performance is viewed within various job categories based on their width (processor request size) and length (job duration), some consistent trends may be observed. Using insights gleaned by the characterization, we develop a selective reservation strategy for backfill scheduling. We demonstrate that the new scheme is better than both conservative and aggressive backfilling. We also consider the issue of fairness in job scheduling and develop a new quantitative approach to its characterization. We show that the newly proposed schemes are also comparable or better than aggressive backfilling with respect to the fairness criterion.

Supported in part by a grant from Sandia National Laboratories.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. K. Aida. Effect of Job Size Characteristics on Job Scheduling Performance. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 1–17, 2000. 56

    Google Scholar 

  2. O. Arndt, B. Freisleben, T. Kielmann, and F. Thilo. A Comparative Study of Online Scheduling Algorithms for Networks of Workstations. Cluster Computing, 3(2):95–112, 2000. 56

    Article  Google Scholar 

  3. P. J. Keleher D. Perkovic. Randomization, Speculation, and Adaptation in Batch Schedulers. In Supercomputing, 2000. 56

    Google Scholar 

  4. D.G. Feitelson. Logs of real parallel workloads from production systems. http://www.cs.huji.ac.il/labs/parallel/workload/logs.html. 56, 57

  5. D.G. Feitelson. Analyzing the Root Causes of Performance Evaluation Results. Technical report 2002-4, Leibniz Center, Hebrew University, 2002. 69

    Google Scholar 

  6. D.G. Feitelson, L. Rudolph, U. Schwiegelshohn, K.C. Sevcik, and P. Wong. Theory and Practice in Parallel Job Scheduling. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 1–34. 1997. 55, 57

    Google Scholar 

  7. D. Jackson, Q. Snell, and M. J. Clement. Core Algorithms of the Maui Scheduler. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 87–102, 2001. 56

    Google Scholar 

  8. J.P._Jones and B. Nitzberg. Scheduling for Parallel Supercomputing: A Historical Perspective of Achievable Utilization. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 1–16, 1999. 55

    Google Scholar 

  9. P. J. Keleher, D. Zotkin, and D. Perkovic. Attacking the Bottlenecks of Backfilling Schedulers. Cluster Computing, 3(4):245–254, 2000. 56, 70

    Article  Google Scholar 

  10. J. Krallmann, U. Schwiegelshohn, and R. Yahyapour. On the Design and Evaluation of Job Scheduling Algorithms. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 17–42, 1999. 55, 58

    Google Scholar 

  11. D. Lifka. The ANL/IBM SP Scheduling System. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 295–303, 1995. 56

    Google Scholar 

  12. A.W. Mu’alem and D. G. Feitelson. Utilization, Predictability, Workloads, and User Runtime Estimates in Scheduling the IBM SP2 with Backfilling. In IEEE Trans. Par. Distr. Systems, volume 12, pages 529–543, 2001. 55, 56, 58

    Article  Google Scholar 

  13. J. Skovira, W. Chan, H. Zhou, and D. Lifka. The EASY-LoadLeveler API Project. In Wkshp. on Job Sched. Strategies for Parallel Processing, pages 41–47, 1996. 55, 56

    Google Scholar 

  14. S. Srinivasan, R. Kettimuthu, V. Subramani, and P. Sadayappan. Characterization of Backfilling Strategies for Parallel Job Scheduling. In Proceedings of the ICPP-2002 Workshops, pages 514–519, 2002. 69

    Google Scholar 

  15. A. Streit. On Job Scheduling for HPC-Clusters and the dynP Scheduler. In Proc. Intl. Conf. High Perf. Comp., pages 58–67, 2001. 56

    Google Scholar 

  16. D. Talby and D. G. Feitelson. Supporting Priorities and Improving Utilization of the IBM SP Scheduler Using Slack-Based Backfilling. In Proceedings of the 13th International Parallel Processing Symposium, pages 513–517, 1999. 56, 70

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Srinivasan, S., Kettimuthu, R., Subramani, V., Sadayappan, P. (2002). Selective Reservation Strategies for Backfill Job Scheduling. In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 2002. Lecture Notes in Computer Science, vol 2537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36180-4_4

Download citation

  • DOI: https://doi.org/10.1007/3-540-36180-4_4

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00172-0

  • Online ISBN: 978-3-540-36180-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics