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Memory usage in the LANL CM-5 workload

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Job Scheduling Strategies for Parallel Processing (JSSPP 1997)

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Abstract

It is generally agreed that memory requirements should be taken into account in the scheduling of parallel jobs. However, so far the work on combined processor and memory scheduling has not been based on detailed information and measurements. To rectify this problem, we present an analysis of memory usage by a production workload on a large parallel machine, the 1024-node CM-5 installed at Los Alamos National Lab. Our main observations are

  • - The distribution of memory requests has strong discrete components, i.e. some sizes are much more popular than others.

  • - Many jobs use a relatively small fraction of the memory available on each node, so there is some room for time slicing among several memory-resident jobs.

  • - Larger jobs (using more nodes) tend to use more memory, but it is difficult to characterize the scaling of per-processor memory usage.

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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. G. M. Amdahl, “Validity of the single processor approach to achieving large scale computer capabilities”. In AFIPS Spring Joint Comput. Conf., vol. 30, pp. 483–485, Apr 1967.

    Google Scholar 

  3. D. C. Burger, R. S. Hyder, B. P. Miller, and D. A. Wood, “Paging tradeoffs in distributed-shared-memory multiprocessors”. J. Supercomput. 10(1), pp. 87–104, 1996.

    Article  Google Scholar 

  4. J. J. Dongarra, H. W. Meuer, and E. Strohmaier, “Top500 supercomputer sites”. http://www.netlib.org/benchmark/top500.html. (updated every 6 months).

    Google Scholar 

  5. 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 

  6. 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 

  7. D. G. Feitelson and M. A. Jette, “Improved utilization and responsiveness with gang 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 

  8. 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 

  9. 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 

  10. D. G. Feitelson and L. Rudolph, “Toward convergence in job schedulers for parallel supercomputers”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 1–26, Springer-Verlag, 1996. Lecture Notes in Computer Science Vol. 1162.

    Google Scholar 

  11. J. L. Gustafson, “Reevaluating Amdahl's law”. Comm. ACM 31(5), pp. 532–533, May 1988. See also Comm. ACM 32(2), pp. 262–264, Feb 1989, and Comm. ACM 32(8), pp. 1014–1016, Aug 1989.

    Article  Google Scholar 

  12. J. L. Gustafson, G. R. Montry, and R. E. Benner, “Development of parallel methods for a 1024-processor hypercube”. SIAM J. Sci. Statist. Comput. 9(4), pp. 609–638, Jul 1988.

    Article  MathSciNet  Google Scholar 

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

    Google Scholar 

  14. Minnesota Supercomputer Center, Inc., The Distributed Job Manager Administration Guide. 1993. ftp://ec.msc.edu/pub/LIGHTNING/djm-1.0.O-Src.tar.Z.

    Google Scholar 

  15. E. W. Parsons and K. C. Sevcik, “Coordinated allocation of memory and processors in multiprocessors”. In SIGMETRICS Conf. Measurement & Modeling of Comput. Syst., pp. 57–67, May 1996.

    Google Scholar 

  16. V. G. J. Peris, M. S. Squillante, and V. K. Naik, “Analysis of the impact of memory in distributed parallel processing systems”. In SIGMETRICS Conf. Measurement & Modeling of Comput. Syst., pp. 5–18, May 1994.

    Google Scholar 

  17. S. K. Setia, “The interaction between memory allocation and adaptive partitioning in message-passing multicomputers”. In Job Scheduling Strategies for Parallel Processing, D. G. Feitelson and L. Rudolph (eds.), pp. 146–165, Springer-Verlag, 1995. Lecture Notes in Computer Science Vol. 949.

    Google Scholar 

  18. J. P. Singh, J. L. Hennessy, and A. Gupta, “Scaling parallel programs for multiprocessors: methodology and examples”. Computer 26(7), pp. 42–50, Jul 1993.

    Article  Google Scholar 

  19. X-H. Sun and L. M. Ni, “Scalable problems and memory-bounded speedup”. J. Parallel & Distributed Comput. 19(1), pp. 27–37, Sep 1993.

    Google Scholar 

  20. Thinking Machines Corp., Connection Machine CM-5 Technical Summary. Nov 1992.

    Google Scholar 

  21. K. Y. Wang and D. C. Marinescu, “Correlation of the paging activity of individual node programs in the SPMD execution model”. In 28th Hawaii Intl. Conf. System Sciences, vol. I, pp. 61–71, Jan 1995.

    Google Scholar 

  22. P. H. Worley, “The effect of time constraints on scaled speedup”. SIAM J. Sci. Statist. Comput. 11(5), pp. 838–858, Sep 1990.

    Article  Google Scholar 

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Dror G. Feitelson Larry Rudolph

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© 1997 Springer-Verlag Berlin Heidelberg

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Feitelson, D.G. (1997). Memory usage in the LANL CM-5 workload. 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_17

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  • DOI: https://doi.org/10.1007/3-540-63574-2_17

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  • Online ISBN: 978-3-540-69599-8

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