Abstract
In this paper we have characterized the inter-arrival time and service time distributions for jobs at a large MPP supercomputing center. Our findings show that the distributions are dispersive and complex enough that they require Hyper Erlang distributions to capture the first three moments of the observed workload. We also present the parameters from the characterization so that they can be easily used for both theoretical studies and the simulations of various scheduling algorithms.
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References
A. Tucker and A. Gupta, “Process control and scheduling issues for multiprogrammed shared-memory multiprocessors,” in Proceedings of the 12th. ACM Symposium on Operating Systems Principle, pp. 159–166,1989.
D. Feitelson and L. Rudolph, “Mapping and scheduling in a shared parallel environment using distributed hierarchical control,” in Intl. Conf Parallel Processing, pp. 1–8, 1990.
D. G. Feitelson, “Packing schemes for gang scheduling,” in Job Scheduling Strategies for Parallel Processing Springer-Verlag, LNCS Vol. 1162, Apr 1996, pp. 89–110,1996.
F. Wang, H. Franke, M. Papaefthymiou, P Pattnaik, L. Rudolph, and M. S. Squillante, “A gang scheduling design for multiprogrammed parallel computing environments,” in Job Scheduling Strategies for Parallel Processing Springer-Verlag, LNCS Vol. 1162, Apr 1996, pp. 111–125,1996.
M. S. Squillante, F. Wang, and M. Papaefthymiou, “An analysis of gang scheduling for multiprogrammed parallel computing environments,” in Proceedings of the Annual ACM Symposium on Parallel Algorithms and Architectures (SPAA), pp. 89–98, 1996.
H. Franke, P Pattnaik, and L. Rudolph, “Gang scheduling for highly efficient distributed multiprocessor systems,” in Proceedings of the 6th Symposium on the Frontiers of Massively Parallel Computation, Annapolis, MD, pp. 1–9, 1996.
D. R. Cox, “A use of complex probabilities in the theory of stochastic process,” Proc. Cambridge Philos. Soc, 1955.
M. F. Neuts, Matrix-Geometric Solutions in Stochastic Models. The John Hopkins University Press, 1981.
M. A. Johnson and M. R. Taaffe, “Matching moments to phase distributions,” Commun. Stat. Stochastics Models, vol. 5, pp. 711–743, 1989.
R. Schassberger, “Insensitivity of steady-state distributions of generalized semi-markov processes i,” Ann. Prob., pp. 87–99,1977.
R. Schassberger, “Insensitivity of steady-state distributions of generalized semi-markov processes ii,” Ann. Prob., pp. 85–93, 1978.
R. Schassberger, “Insensitivity of steady-state distributions of generalized semi-markov processes with speeds,” Adv. Appl. Prob., pp. 836–851,1978.
R. Schassberger, “The insensitivity of stationary probabilities in networks of queues,” Adv. Appl. Prob., pp. 906–912, 1978.
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© 1997 Springer-Verlag Berlin Heidelberg
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Jann, J., Pattnaik, P., Franke, H., Wang, F., Skovira, J., Riordan, J. (1997). Modeling of workload in MPPs. 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_18
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DOI: https://doi.org/10.1007/3-540-63574-2_18
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