Advertisement

Applying Processes Rescheduling over Irregular BSP Application

  • Rodrigo da Rosa Righi
  • Laércio Lima Pilla
  • Alexandre Silva Carissimi
  • Philippe O. A. Navaux
  • Hans-Ulrich Heiss
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5544)

Abstract

This paper shows an evaluation of processes rescheduling over an irregular BSP (Bulk Synchronous Parallel) application. Such application is based on dynamic programming and its irregularity is presented through the variation of computation density along the matrix’ cells. We are using MigBSP model for processes rescheduling, which combines multiple metrics - Computation, Communication and Memory - to decide about processes migration. The main contribution of this paper includes the viability to use processes migration on irregular BSP applications. Instead to adjust the load of each process by hand, we presented that automatic processes rebalancing is an effortless technique to obtain performance. The results showed gains greater than 10% over our multi-cluster architecture. Moreover, an acceptable overhead from MigBSP was observed when no migrations happen during application execution.

Keywords

Process Migration Migration Cost Application Execution Adaptive Load Destination Processor 
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.

References

  1. 1.
    Vadhiyar, S.S., Dongarra, J.J.: Self adaptivity in grid computing: Research articles. Concurr. Comput.: Pract. Exper. 17(2-4), 235–257 (2005)CrossRefGoogle Scholar
  2. 2.
    Bonorden, O., Gehweiler, J., auf der Heide, F.M.: Load balancing strategies in a web computing environment. In: Conf. on Parallel Processing and Applied Mathematics, pp. 839–846 (2005)Google Scholar
  3. 3.
    Righi, R., Pilla, L., Carissimi, A., Navaux, P.O.A.: Controlling processes reassignment in bsp applications. In: 20th International Symposium on Computer Architecture and high Performance Computing, pp. 37–44. IEEE, Los Alamitos (2008)CrossRefGoogle Scholar
  4. 4.
    Low, M.Y.H., Liu, W., Schmidt, B.: A parallel bsp algorithm for irregular dynamic programming. In: Xu, M., Zhan, Y.-W., Cao, J., Liu, Y. (eds.) APPT 2007. LNCS, vol. 4847, pp. 151–160. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Smith, T.F., Waterman, M.S.: Identification of common molecular subsequences. Journal of Molecular Biology 147(1), 195–197 (1981)CrossRefGoogle Scholar
  6. 6.
    Casanova, H., Legrand, A., Quinson, M.: Simgrid: A generic framework for large-scale distributed experiments. In: Conf. Comp. Modeling and Simulation, pp. 126–131. IEEE, Los Alamitos (2008)Google Scholar
  7. 7.
    Huang, C., Zheng, G., Kale, L., Kumar, S.: Performance evaluation of adaptive mpi. In: Symp. on Principles and pract. of parallel programming, pp. 12–21. ACM Press, New York (2006)Google Scholar
  8. 8.
    Moreno-Vozmediano, R., Alonso-Conde, A.B.: Influence of grid economic factors on scheduling and migration. In: Daydé, M., Dongarra, J., Hernández, V., Palma, J.M.L.M. (eds.) VECPAR 2004. LNCS, vol. 3402, pp. 274–287. Springer, Heidelberg (2005)Google Scholar
  9. 9.
    Bhandarkar, M.A., Brunner, R., Kale, L.V.: Run-time support for adaptive load balancing. In: IPDPS 2000: Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing, pp. 1152–1159. Springer, London (2000)Google Scholar
  10. 10.
    Jiang, Y., Tong, W., Zhao, W.: Resource load balancing based on multi-agent in servicebsp model. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2007 (3). LNCS, vol. 4489, pp. 42–49. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Bonorden, O.: Load balancing in the bulk-synchronous-parallel setting using process migrations. In: Symp. on Parallel and Distrib. Processing, pp. 1–9. IEEE, Los Alamitos (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Rodrigo da Rosa Righi
    • 1
  • Laércio Lima Pilla
    • 1
  • Alexandre Silva Carissimi
    • 1
  • Philippe O. A. Navaux
    • 1
  • Hans-Ulrich Heiss
    • 2
  1. 1.Instituto de InformáticaFederal University of Rio Grande do SulBrazil
  2. 2.Kommunikations- und BetriebssystemeTechnical University BerlinGermany

Personalised recommendations