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On the Use of Services to Support Numerical Weather Prediction

  • Jay Alameda
  • Albert L. Rossi
  • Shawn Hampton
Conference paper
Part of the IFIP The International Federation for Information Processing book series (IFIPAICT, volume 239)

Abstract

The challenges of building an effective grid-based problem solving environment that truly extends and embraces a computational scientist’s traditional tools are multifold. It is far too easy to build simple stovepipes that allow fixed use patterns, that don’t extend a scientist’s desktop, and fail to encompass the full range of patterns that a scientist needs to find such a problem-solving environment as a liberating and enabling tool. In the LEAD project, we have focused on the most challenging users of numerical weather prediction, namely, the atmospheric science researchers, who are prone to use their own tools, their own modified versions of community codes such as the Weather Research and Forecasting (WRF) model, and are typically comfortable with elaborate shell scripts to perform the work they find to be necessary to succeed, to drive our development efforts. Our response to these challenges includes a multi-level workflow engine, to handle both the challenges of ensemble description and execution, as well as the detailed patterns of workflow on each computational resource; services to support the peculiarities of each platform being used to do the modeling (such as on TeraGrid), and the use of an RDF triple store and message bus together as the backbone of our notification, logging, and metadata infrastructure. The design of our problem-solving environment elements attempts to come to grips with lack of control of elements surrounding and supporting the environment; we achieve this through multiple mechanisms including using the OSGI plug-in architecture, as well as the use of RDF triples as our finest-grain descriptive element. This combination, we believe, is an important stepping stone to building a cyber environment, which aims to provide flexibility and ease of use far beyond the current range of typical problem solving environments.

Keywords

Numerical Weather Prediction Grid Resource Execution Service Correct Environment Java Messaging Service 
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. [WRF]
    The Weather Research & Forecasting Website, http://www.wrf-model. org/index.php.
  2. [LEAD]
    Droegemeier, K.K. and Co-Authors, 2004: Linked environments for atmospheric discovery (LEAD): A cyberinfrastructure for mesoscale meteorology research and education. Preprints, 20th Conf. on Interactive Info. Processing Systems for Meteorology, Oceanography, and Hydrology, Seattle, WA, Amer. Meteor. SocGoogle Scholar
  3. [Globus]
    The Globus Toolkit, http://www.globus.org/toolkit/.
  4. [grid]
    Grid Computing, Wikipedia, the free encyclopedia, http://www.en.wikip edia.org/wiki/Gridcomputing.
  5. [TeraGrid]
  6. [Siege]
  7. [JMS]
  8. [ActiveMQ]
  9. [LMS]
    LEAD Metadata Schema Repository, http://www.extreme.indiana.edu/rescat/metadata/.
  10. [RCP]
  11. [jglobus]
  12. [myproxy]
    Myproxy Credential Management Service, http://www.grid.ncsa.uiuc.edu/myproxy/
  13. [TeraGrid]
  14. [IDV]
    Unidata Integrated Data Viewer (IDV), http://www.unidata.ucar.edu/software/idv/.
  15. [UnidataWorkshop]
    2006 Unidata Users Workshop: Expanding the Use of Models as Educational Tools in the Atmospheric & Related Sciences, http://www.unidata.ucar. edu/community/2006workshop/
  16. [RSL]

Copyright information

© International Federation for Information Processing 2007

Authors and Affiliations

  • Jay Alameda
    • 1
  • Albert L. Rossi
    • 1
  • Shawn Hampton
    • 1
  1. 1.National Center for Supercomputing ApplicationsUniversity of Illinois at Urbana-ChampaignUrbana

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