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Software for parallel computing: the LAM implementation of MPI

Author

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  • Christopher A. Swann

    (Department of Economics, SUNY-Stony Brook, Stony Brook,NY 11794, USA)

Abstract

Many econometric problems can benefit from the application of parallel computing techniques, and recent advances in hardware and software have made such application feasible. There are a number of freely available software libraries that make it possible to write message passing parallel programs using personal computers or Unix workstations. This review discusses one of these-the LAM (Local Area Multiprocessor) implementation of MPI (the Message Passing Interface). Copyright © 2001 John Wiley & Sons, Ltd.

Suggested Citation

  • Christopher A. Swann, 2001. "Software for parallel computing: the LAM implementation of MPI," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 185-194.
  • Handle: RePEc:jae:japmet:v:16:y:2001:i:2:p:185-194
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    File URL: http://qed.econ.queensu.ca:80/jae/2001-v16.2/
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    References listed on IDEAS

    as
    1. Nagurney, Anna, 1996. "Parallel computation," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 7, pages 335-404, Elsevier.
    2. Liu, Chuanhai & Rubin, Donald B., 1996. "Markov-Normal analysis of iterative simulations before their convergence," Journal of Econometrics, Elsevier, vol. 75(1), pages 69-78, November.
    3. Coleman, Wilbur John, II, 1993. "Solving Nonlinear Dynamic Models on Parallel Computers," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 325-330, July.
    4. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, December.
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    Cited by:

    1. Michael S. Delgado & Christopher F. Parmeter, 2013. "Embarrassingly Easy Embarrassingly Parallel Processing in R: Implementation and Reproducibility," Working Papers 2013-06, University of Miami, Department of Economics.
    2. Christopher Ferrall, 2005. "Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution," Computational Economics, Springer;Society for Computational Economics, vol. 25(4), pages 343-379, June.

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