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Effective Selection of Partition Sizes for Moldable Scheduling of Parallel Jobs

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2552))

Abstract

Although the current practice in parallel job scheduling requires jobs to specify a particular number of requested processors, most parallel jobs are moldable, i.e. the required number of processors is flexible. This paper addresses the issue of effective selection of processor partition size for moldable jobs. The proposed scheduling strategy is shown to provide significant benefits over a rigid scheduling model and is also considerably better than a previously proposed approach to moldable job scheduling.

Supported in part by a grant from Sandia National Laboratories.

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References

  1. S. V. Anastasiadis and K. C. Sevcik. Parallel Application Scheduling on Networks of Workstations. Journal of Parallel and Distributed Computing, 43(2): 109–124, 1997. 174

    Article  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. 174

    Article  Google Scholar 

  3. S. H. Chiang, R. K. Mansharamani, and M. K. Vernon. Use of Application Characteristics and Limited Preemption for Run-to-Completion Parallel Processor Scheduling Policies. In SIGMETRICS, pages 33–44, 1994. 174

    Google Scholar 

  4. S. H. Chiang and M. K. Vernon. Production Job Scheduling for Parallel Shared Memory Systems. In Proceedings of the International Parallel and Distributed Processing Symp, 2001. 174

    Google Scholar 

  5. W. Cirne. Using Moldability to Improve the Performance of Supercomputer Jobs. Ph.D. Thesis. Computer Science and Engineering, University of California San Diego, 2001. 174, 176

    Google Scholar 

  6. W. Cirne. When the Herd is Smart: The Emergent Behavior of SA. In IEEE Trans. Par. Distr. Systems, 2002. 174, 176

    Google Scholar 

  7. W. Cirne and F. Berman. Adaptive Selection of Partition Size for Supercomputer Requests. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 187–208, 2000. 174, 176

    Google Scholar 

  8. A. B. Downey. A Model For Speedup of Parallel Programs. Technical Report CSD-97-933. University of California at Berkeley, 1997. 176

    Google Scholar 

  9. D. G. Feitelson. Logs of real parallel workloads from production systems. http://www.cs.huji.ac.il/labs/parallel/workload/logs.html. 175, 176

  10. 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. 174, 176

    Google Scholar 

  11. D. Jackson, Q. Snell, and M. J. Clement. Core Algorithms of the Maui Scheduler. In Wkshp. on Job Sched. Strategies for Parallel Processing, pages 87–102, 2001. 175

    Google Scholar 

  12. P. J. Keleher, D. Zotkin, and D. Perkovic. Attacking the Bottlenecks of Backfilling Schedulers. Cluster Computing, 3(4):245–254, 2000. 174

    Article  Google Scholar 

  13. D. Lifka. The ANL/IBM SP Scheduling System. In Workshop on Job Scheduling Strategies for Parallel Processing, pages 295–303, 1995. 175

    Google Scholar 

  14. 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. 174, 175

    Article  Google Scholar 

  15. E. Rosti, E. Smirni, L. W. Dowdy, G. Serazzi, and B. M. Carlson. Robust Partitioning Policies of Multiprocessor Systems. Performance Evaluation, 19(2–3):141–165, 1994. 174

    Article  Google Scholar 

  16. S. Setia and S. Tripathi. A Comparative Analysis of Static Processor Partitioning Policies for Parallel Computers. In Proc. of the Intl. Wkshp. on Modeling and Simulation of Computer and Telecomm. Syst. (MASCOTS), pages 283–286, 1993. 174

    Google Scholar 

  17. K. C. Sevcik. Application Scheduling and Processor Allocation in Multiprogrammed Parallel Processing Systems. Performance Evaluation, 19(2–3):107–140, 1994. 174

    Article  MATH  Google Scholar 

  18. 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. 175

    Google Scholar 

  19. S. Srinivasan, R. Kettimuthu, V. Subramani, and P. Sadayappan. Characterization of Backfilling Strategies for Parallel Job Scheduling. In Proceedings of the ICPP2002 Workshops, pages 514–519, 2002. 180

    Google Scholar 

  20. S. Srinivasan, R. Kettimuthu, V. Subramani, and P. Sadayappan. Selective Reservation Strategies for Backfill Job Scheduling. In Proceedings of the 8th Workshop on Job Scheduling Strategies for Parallel Processing, 2002. 180

    Google Scholar 

  21. A. Streit. On Job Scheduling for HPC-Clusters and the dynP Scheduler. In Proc. Intl. Conf. High Perf. Comp., pages 58–67, 2001. 174

    Google Scholar 

  22. D. Talby and D. Feitelson. Supporting Priorities and Improving Utilization of the IBM SP Scheduler Using Slack-Based Backfilling. In Proceedings of the 13th International Parallel Processing Symposium, 1999. 175

    Google Scholar 

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© 2002 Springer-Verlag Berlin Heidelberg

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Srinivasan, S., Subramani, V., Kettimuthu, R., Holenarsipur, P., Sadayappan, P. (2002). Effective Selection of Partition Sizes for Moldable Scheduling of Parallel Jobs. In: Sahni, S., Prasanna, V.K., Shukla, U. (eds) High Performance Computing — HiPC 2002. HiPC 2002. Lecture Notes in Computer Science, vol 2552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36265-7_17

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  • DOI: https://doi.org/10.1007/3-540-36265-7_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00303-8

  • Online ISBN: 978-3-540-36265-4

  • eBook Packages: Springer Book Archive

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