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A Beowulf Cluster for Computational Chemistry

  • K. A. Hawick
  • D. A. Grove
  • P. D. Coddington
  • H. A. James
  • M. A. Buntine
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1823)

Abstract

We have constructed a Beowulf cluster of networked PCs that is dedicated to solving chemistry problems using standard software packages such as Gaussian and GAMESS. We describe the economic and performance trade-offs in the design of the cluster, and present some some selected benchmark results for a parallel version of GAMESS. We believe that the Beowulf we have constructed offers the best price/performance ratio for our chemistry applications, and that commodity clusters can now provide dedicated supercomputer performance within the budget of most university departments.

Keywords

Parallel Version Standard Software Package Beowulf Cluster Distribute Memory Architecture Shared Memory Programming 
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.

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References

  1. 1.
    Distributed and High-Performance Computing Group, University of Adelaide, Perseus: A Beowulf for computational chemistry, http://dhpc.adelaide.edu.au/projects/beowulf/perseus.html.
  2. 2.
    Gaussian, Inc., Gaussian, http://www.gaussian.com/.
  3. 3.
    Gordon Research Group, Iowa State University, GAMESS-US, http://www.msg.ameslab.gov/GAMESS/GAMESS.html.
  4. 4.
    Computing for Science Ltd, GAMESS-UK, http://www.dl.ac.uk/CFS/.
  5. 5.
    The Condor Project, University of Wisconsin, Condor: High Throughput Computing, http://www.cs.wisc.edu/condor/.
  6. 6.
    NASA CESDIS, Beowulf Project, http://www.beowulf.org/.
  7. 7.
    Scientific Computing Associates, Linda, http://www.sca.com/linda.html.
  8. 8.
    M.F. Guest, Performance of Various Computers in Computational Chemistry, Proc. of the Daresbury Machine Evaluation Workshop, Nov 1996. Updated version available at http://www.dl.ac.uk/CFS/benchmarks/compchem.html, June 1999.
  9. 9.
    M.C. Nicklaus et al., Computational Chemistry on Commodity-Type Computers, Journal of Chemical and Information Computer Sciences, 1998, 38:5, 893–905.CrossRefGoogle Scholar
  10. 10.
    M.F. Guest, P. Sherwood and J.A. Nichols, Massive Parallelism: The Hardware for Computational Chemistry?, http://www.dl.ac.uk/CFS/parallel/MPP/mpp.html.

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • K. A. Hawick
    • 1
  • D. A. Grove
    • 1
  • P. D. Coddington
    • 1
  • H. A. James
    • 1
  • M. A. Buntine
    • 2
  1. 1.Department of Computer ScienceUniversity of AdelaideAustralia
  2. 2.Department of ChemistryUniversity of AdelaideAustralia

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