Modeling and Experimental Validation of the Data Handover API

  • Soumeya Leila Hernane
  • Jens Gustedt
  • Mohamed Benyettou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6646)

Abstract

Data Handover, DHO, is a general purpose API for an efficient management for locking and mapping data. Through objects called lock handles, it enables to control resources in a distributed setting. Such handles ease the access to data for client code, by ensuring data consistency and efficiency at the same time. This paper explores DHO as it was presented in [1]. We model the phases that a lock handle crosses to achieve a DHO locking/mapping life cycle. The Grid Reality And Simulation (GRAS) environment of SimGrid is used as a support of an implementation of DHO and a series of tests and benchmarks of that implementation is presented. GRAS has the advantage of allowing the execution in either the simulator or on a real platform. For that purpose, we exploited a cluster of Grid’5000. The experiments that carried out cover various scenarios of sequences to lock a resources (inclusive or exclusive locking only, or combinations of both) and of combining different architectural factors. The tests demonstrate the ability of DHO to provide a robust and scalable framework. The good evaluation of the present work is consistent with an analysis of the expected behavior done by queuing theory.

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References

  1. 1.
    Gustedt, J.: Data handover: Reconciling message passing and shared memory. In: Fiadeiro, J.L., Montanari, U., Wirsing, M. (eds.) Foundations of Global Computing, Dagstuhl, Germany. Dagstuhl Seminar Proceedings, (05081) (2006), http://drops.dagstuhl.de/opus/volltexte/2006/297
  2. 2.
    The OpenMP API specification for parallel programming, http://www.openmp.org
  3. 3.
    Arquet, P.: Introduction à MPI – Message Passing Interface (2001), http://www2.lifl.fr/west/courses/cshp/mpi.pdf
  4. 4.
  5. 5.
    Clauss, P.-N., Gustedt, J.: Iterative computations with ordered read-write locks. Journal of Parallel and Distributed Computing 70(5), 496–504 (2010)CrossRefMATHGoogle Scholar
  6. 6.
    Clauss, P.-N., Gustedt, J.: Experimenting iterative computations with ordered read-write locks. In: Danelutto, M., Gross, T., Bourgeois, J. (eds.) 18th Euromicro International Conference on Parallel, Distributed and network-based Processing, pp. 155–162. IEEE, Italy Pisa (2010)Google Scholar
  7. 7.
    Gustedt, J., Vialle, S., De Vivo, A.: The parXXL environment: Scalable fine grained development for large coarse grained platforms. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds.) PARA 2006. LNCS, vol. 4699, pp. 1094–1104. Springer, Heidelberg (2007), http://hal-supelec.archives-ouvertes.fr/hal-00280094/en/ CrossRefGoogle Scholar
  8. 8.
    Quinson, M., Vernier, F.: Byte-range asynchronous locking in distributed settings. In: 17th Euromicro International Conference on Parallel, Distributed and network-based Processing - PDP 2009, Weimar, Germany (2009), http://hal.inria.fr/inria-00338189/en/
  9. 9.
    Sipser, M.: Introduction to the Theory of Computation. PWS, Boston (1997)MATHGoogle Scholar
  10. 10.
    Smith, W., Taylor, V., Foster, I.: Using run-time predictions to estimate queue wait times and improve scheduler performance. In: Feitelson, D.G., Rudolph, L. (eds.) JSSPP 1999, IPPS-WS 1999, and SPDP-WS 1999. LNCS, vol. 1659, pp. 202–219. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  11. 11.
    Casanova, H., Legrand, A., Quinson, M.: SimGrid: a generic framework for large-scale distributed experiments. In: IEEE International Conference on Computer Modeling and Simulation - EUROSIM / UKSIM 2008. IEEE, Cambrige (2008), http://hal.inria.fr/inria-00260697/en/ Google Scholar
  12. 12.
    Velho, P., Legrand, A.: Accuracy study and improvement of network simulation in the SimGrid framework. In: Simutools 2009, pp. 1–10. ICST, Brussels (2009)Google Scholar
  13. 13.
    Little, J.D.: A proof for the queuing formula: L = λW. Operations Research 3(9), 383–387 (1961)MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Soumeya Leila Hernane
    • 1
    • 2
  • Jens Gustedt
    • 2
  • Mohamed Benyettou
    • 1
  1. 1.University of Science and Technology of Oran USTOAlgeria
  2. 2.INRIA Nancy – Grand EstFrance

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