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Automation and Remote Control

, Volume 68, Issue 5, pp 750–759 | Cite as

Productivity prediction of MPI programs based on models

  • A. I. Avetisyan
  • S. S. Gaisaryan
  • V. P. Ivannikov
  • V. A. Padaryan
Topical Issue

Abstract

A model of parallel program that can be effectively interpreted on the development computer guaranteeing the possibility of a sufficiently precise prediction of real run time for a simulated parallel program at the prescribed computer system is studied. The model is worked out for parallel programs with explicit message passing written in the Java language with MPI library access and is included into the composition of ParJava environment. The model is obtained by transforming the program control tree that can be constructed for Java programs by modifying the abstract syntax tree. To model communication functions, the model LogGP is used which allows taking into consideration the specific character of the communication network of the distributed computer system.

PACS number

07.05.Tp 

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References

  1. 1.
    Report of the President’s Information Technology Advisory Committee (PITAC) to the President on Computational Science: Ensuring America’s Competitiveness, manuscript is available at: http://www.nitrd.gov/pitac/reports/.
  2. 2.
    National Targer Program DARPA. High Productivity Computing Systems (HPCS), manuscript is available at: http://www.highproductivity.org/.
  3. 3.
    Ivannikov, V.P., Gaisaryan, S.S., Avetisyan, A.I., and Padaryan, V.A., Estimation of Dynamical Characteristics of a Parallel Program on a Model, Program. Comput. Software, 2006, vol. 32, no. 4, pp. 203–214.CrossRefGoogle Scholar
  4. 4.
    Ivannikov, V.P., Gaisaryan, S.S., Avetisyan, A.I., and Padaryan, V.A., Improving Properties of a Parallel Program in ParJava Environment, Proc. EuroPVM/MPI Conf., 2003, vol. 2840, pp. 491–494.Google Scholar
  5. 5.
    Alexandrov, A., Ionescu, M.F., Schauser, K.E., and Scheiman, Chr., LogGP: Incorporating Long Messages into the LogP Model—One Step Closer towards a Realistic Model for Parallel Computation, Technical Report: TRCS95-09, University of California at Santa Barbara, 1995.Google Scholar
  6. 6.
    Gosling, J., Joy, B., Steele, G., and Bracha, G., The Java Language Specification, New York: Addison-Wesley, 2005.Google Scholar
  7. 7.
    Prakash, S. and Bagrodia, R., MPI-Sim: Using Parallel Simulation to Evaluate MPI Programs, Proc. Winter Simulat. Conf., 1998, pp. 467–474.Google Scholar
  8. 8.
    Al-Tawil, Kh. and Moritz, C.A., Performance Modeling and Evaluation of MPI, J. Paral. Distribut. Comput., 2001, vol. 61, no. 2, pp. 202–223.zbMATHCrossRefGoogle Scholar
  9. 9.
    Martin, R.P., Vahdat, A.M., Culler, D.E., and Anderson, T.E., Effects of Communication Latency, Overhead, and Bandwidth in a Cluster Architecture, Proc. 24 Ann. Int. Symp. Comput. Architecture, Denver, 1997, pp. 85–97.Google Scholar
  10. 10.
    Information Analytic Center of Parallel Computation, manuscript is available at: http://www. parallel.ru/.

Copyright information

© Pleiades Publishing, Ltd. 2007

Authors and Affiliations

  • A. I. Avetisyan
    • 1
  • S. S. Gaisaryan
    • 1
  • V. P. Ivannikov
    • 1
  • V. A. Padaryan
    • 1
  1. 1.Institute for System ProgrammingRussian Academy of SciencesMoscowRussia

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