Advertisement

Applying Grid Computing to the Parameter Sweep of a Group Difference Pseudopotential

  • Wibke Sudholt
  • Kim K. Baldridge
  • David Abramson
  • Colin Enticott
  • Slavisa Garic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3036)

Abstract

Theoretical modeling of chemical and biological processes is a key to understand nature and to predict experiments. Unfortunately, this is very data and computation extensive. However, the worldwide computing grid can now provide the necessary resources. Here, we present a coupling of the GAMESS quantum chemical code to the Nimrod/G grid distribution tool, which is applied to the parameter scan of a group difference pseudopotential (GDP). This represents the initial step in parameterization of a capping atom for hybrid quantum mechanics-molecular mechanics (QM/MM) calculations. The results give hints to the physical forces of functional group distinctions and starting points for later parameter optimizations. The demonstrated technology significantly extends the manageability of accurate, but costly quantum chemical calculations and is valuable for many applications involving thousands of independent runs.

Keywords

Grid Resource Grid Technology Parameter Sweep Functional Group Distinction Plan File 
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.
    Zhang, Y., Lee, T.-S., Yang, W.: A Pseudobond Approach to Combining Quantum Mechanical and Molecular Mechanical Methods. J. Chem. Phys. 110, 46–54 (1999)CrossRefGoogle Scholar
  2. 2.
    Sudholt, W., Baldridge, K.K., Abramson, D., Enticott, C., Garic, S.: Parameter Scan of an Effective Group Difference Pseudopotential Using Grid Computing. New Generation Computing 22, 125–136 (2004)CrossRefGoogle Scholar
  3. 3.
    Schmidt, M.W., Baldridge, K.K., Boatz, J.A., Elbert, S.T., Gordon, M.S., Jensen, J.H., Koseki, S., Matsunaga, N., Nguyen, K.A., Su, S.J., Windus, T.L., Dupuis, M., Montgomery, J.A.: General Atomic and Molecular Electronic-Structure System. J. Comput. Chem. 14, 1347–1363 (1993), http://www.msg.ameslab.gov/GAMESS/GAMESS.html CrossRefGoogle Scholar
  4. 4.
    Abramson, D., Sosic, R., Giddy, J., Hall, B.: Nimrod: A Tool for Performing Parametised Simulations Using Distributed Workstations. In: The 4th IEEE Symposium on High Performance Distributed Computing, Virginia (August 1995); Abramson, D., Giddy, J., Kotler, L.: High Performance Parametric Modeling with Nimrod/G: Killer Application for the Global Grid? In: International Parallel and Distributed Processing Symposium (IPDPS), Cancun, Mexico, May 2000, pp. 520–528 (2000), http://www.csse.monash.edu.au/~davida/nimrod/
  5. 5.
    Foster, I., Kesselman, C. (eds.): The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers, USA (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Wibke Sudholt
    • 1
  • Kim K. Baldridge
    • 1
  • David Abramson
    • 2
  • Colin Enticott
    • 2
  • Slavisa Garic
    • 2
  1. 1.Department of Chemistry & Biochemistry and San Diego Supercomputer Center (SDSC)University of California, San Diego (UCSD)La JollaUSA
  2. 2.Center for Enterprise Distributed Systems (DSTC) and School of Computer Science and Software EngineeringMonash UniversityClaytonAustralia

Personalised recommendations