Advertisement

Analysis of Component Model Extensions to Support the GriCoL Language

Chapter
  • 236 Downloads

Abstract

Nowadays, programming grid applications is still a major challenge. Several systems, tools and environments have appeared to allow end-users to describe applications without dealing with the complexity of the grid infrastructure. An application description in such environments is done through high level languages such as the Grid Concurrent Language (Gricol). Independently of the application domain, this language enables the description of highly complex scientific experiments. While such a high level language is offered to end-users, the question of how to implement it is raised. The contribution of this paper is to analyze the support of a Gricol application within component models, in particular the support of its temporal composition represented by a control flow construction.

Keywords

programming model software component programming language control-flow data-flow GriCoL 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Service Component Architecture Specifications. http://www.osoa.org/.
  2. [2]
    The Triana Project. http://www.trianacode.org.
  3. [3]
    M. Aldinucci, S. Campa, M. Coppola, M. Danelutto, D. Laforenza, D. Puppin, L. Scarponi, M. Vanneschi, and C. Zoccolo. Components for high performance Grid programming in the Grid.it project. In Proc. of the Workshop on Component Models and Systems for Grid Applications (June 2004, Saint Malo, France). Springer, January 2005.Google Scholar
  4. [4]
    G. Antoniu, H.L. Bouziane, L. Breuil, M. Jan, and C. Perez. Enabling transparent data sharing in component models. In 6th IEEE International Symposium on Cluster Computing and the Grid (CCGRID), pages 430-433, Singapore, May 2006.Google Scholar
  5. [5]
    D.E. Bernholdt, B.A. Allan, R. Armstrong, F. Bertrand, K. Chiu, T.L. Dahlgren, K. Damevski, W.R. Elwasif, T.G. W. Epperly, M. Govindaraju, D.S. Katz, J.A. Kohl, M. Krishnan, G. Kumfert, J.W. Larson, S. Lefantzi, M.J. Lewis, A.D. Malony, L.C. McInnes, J. Nieplocha, B. Norris, S.G. Parker, J. Ray, S. Shende, T.L. Windus, and S. Zhou. A component architecture for high-performance scientific computing. Int. Jour-nal of High Performance Computing Applications, November 2005. ACTS Collection special issue.Google Scholar
  6. [6]
    E. Bruneton, T. Coupaye, and J.B. Stefani. Recursive and dynamic software composition with sharing. In Seventh International Workshop on Component-Oriented Programming (WCOP02), Malaga, Spain, June 2002.Google Scholar
  7. [7]
    N. Currle-Linde, F. Boes, and M. Resch. GriCoL: A Language for Scientific Grids. In Proceedings of the 2nd IEEE International Conference on e-Science and Grid Computing, Amsterdam, Netherlands, 2006.Google Scholar
  8. [8]
    R. Lovas, G. Dozsa, P. Kacsuk, N. Podhorszki, and D. Drotos. Workflow support for complex grid applications: Integrated and portal solutions. In Proceedings of the 2nd European Across Grids Conference, pages 129-138, Nicosia, Cyprus, 2004.Google Scholar
  9. [9]
    J. Magee, N. Dulay, and J. Kramer. A Constructive Development Environment for Parallel and Distributed Programs. In Proceedings of the International Workshop on Configurable Distributed Systems, pages 4-14, Pittsburgh, US, March 1994.Google Scholar
  10. [10]
    Partners of the CoreGrid WP3 institute. Proposals for a grid component model. Technical report, February 2006. D.PM.02.Google Scholar
  11. [11]
    OMG. CORBA component model, v4.0. Document formal/2006-04-01, April 2006.Google Scholar
  12. [12]
    W.M.P van der Aalst, A.H.M. ter Hofstede, B. Kiepuszewski, and A.P. Barros. Workflow patterns. Distributed and Parallel Databases, 14(3):5-51, July 2003.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.INRIA/IRISACampus de BeaulieuRennesFrance
  2. 2.High Performance Computing Center Stuttgart (HLRS)University of StuttgartStuttgartGermany

Personalised recommendations