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HMM: A Static Mapping Algorithm to Map Parallel Applications on Grids

  • Ranieri Baraglia
  • Renato Ferrini
  • Pierluigi Ritrovato
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3911)

Abstract

In this paper we present a static mapping heuristic, called Heterogeneous Multi-phase Mapping (HMM), which allows a suboptimal mapping of a parallel program onto a metacomputer to minimize the program execution time. HMM allocates parallel tasks by exploiting the information embedded in the parallelism forms used to implement an application. Moreover, it uses a local search technique together with the tabu search meta-heuristic. The experimental results show that the proposed approach performs well promising a significant potential to develop efficient mapping solutions for metacomputers.

Keywords

Tabu Search Directed Acyclic Graph Mapping Solution Parallel Application Task Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Freund, R.F., Siegel, H.J.: Heterogeneous Processing. IEEE Computer 26(6), 13–17 (1993)Google Scholar
  2. 2.
    Cattlet, C.E., Smarr, L.: Metacomputing. Communication of the ACM 53(6), 45 (1992)Google Scholar
  3. 3.
    Foster, I., Kesselman, C.: The Grid: blueprint for new computing infrastructure. Morgan Kaufmann Publishers, San Francisco (1998)Google Scholar
  4. 4.
    Ali, H.H., El-Rewini, H., Lewis, T.G.: Task Scheduling in Parallel and Distributed Systems. PTR Prentice Hall, Englewood Cliffs (1994)Google Scholar
  5. 5.
    Eshaghian, M.M.: Heterogeneous Computing. Artech House Publishers (1996)Google Scholar
  6. 6.
    Lo, V.M.: Heuristic Algorithms for Task Assignment in Distributed Systems. IEEE Transaction on Computers 37(11), 1384–1397 (1988)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Shen, C., Tsai, W.: A Graph Matching Approach to Optimal Task Assignment in Distributed Computing Systems Using a Minmax Criterion. IEEE Transaction on Computers C-34(3), 197–203 (1985)CrossRefGoogle Scholar
  8. 8.
    Iverson, M.A., Ozguner, F., Follen, G.J.: Parallelizing Existing Applications in a Distributed Heterogeneous Environment. In: Proc. 4th IEEE Heterogeneous Computing Workshop (HCW 1995), pp. 93–100 (1995)Google Scholar
  9. 9.
    Topcuoglu, H., Hariri, S., Wu, M.-Y.: Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing. IEEE Transactions on Parallel and Distributed Systems 13(3) (March 2002)Google Scholar
  10. 10.
    Glover, F., Laguna, M.: Tabu Search. Kluwer Academic Publishers, Boston (1997)CrossRefMATHGoogle Scholar
  11. 11.
    Hey, A.J.G.: Experiments in MIMD Parallelism. In: Odijk, E., Syre, J.-C., Rem, M. (eds.) PARLE 1989. LNCS, vol. 365, Springer, Heidelberg (1989)Google Scholar
  12. 12.
    Gropp, W., Lusk, E., Skjellum, A.: Using MPI Portable Parallel Programming with the Message-Passing Interface. The MIT Press, Cambridge (1999)MATHGoogle Scholar
  13. 13.
    Skillicorn, D.B.: Models for Practical Parallel Computation. International Journal of Parallel Programming 20(2), 133–158 (1991)CrossRefGoogle Scholar
  14. 14.
    Jiang, H., Bhuyan, L.N., Ghosal, D.: Approximate Analysis of Multiprocessing Task Graphs. In: Proceedings of International Conference on Parallel Processing, vol. III, pp. 228–235 (1990)Google Scholar
  15. 15.
    Baraglia, R., Ferrini, R., Ritrovato, P.: A Static Mapping Heuristics to Map Parallel Applications to Heterogeneous Computing Systems. Concurrency: Practice and Experience, 17, 1579–1605 (2005) published onlineGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ranieri Baraglia
    • 1
  • Renato Ferrini
    • 1
  • Pierluigi Ritrovato
    • 2
  1. 1.ISTIInstitute of the Italian National Research CouncilItaly
  2. 2.CRMPAUniversity of SalernoItaly

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