Parallel Computation in Econometrics: A Simplified Approach
AbstractParallel computation has a long history in econometric computing, but is not at all wide spread. We believe that a major impediment is the labour cost of coding for parallel architectures. Moreover, programs for specific hardware often become obsolete quite quickly. Our approach is to take a popular matrix programming language (Ox), and implement a message-passing interface using MPI. Next, object-oriented programming allows us to hide the specific parallelization code, so that a program does not need to be rewritten when it is ported from the desktop to a distributed network of computers. Our focus is on so-called embarrassingly parallel computations, and we address the issue of parallel random number generation.
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Bibliographic InfoPaper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2004-W16.
Length: 32 pages
Date of creation: 30 Jan 2004
Date of revision:
Contact details of provider:
Web page: http://www.nuff.ox.ac.uk/economics/
Code optimization; Econometrics; High-performance computing; Matrix-programming language; Monte Carlo; MPI; Ox; Parallel computing; Random number generation.;
Other versions of this item:
- David Hendry & Neil Shephard & Jurgen Doornik, 2003. "Parallel Computation In Econometrics: A Simplified Approach," Economics Series Working Papers 2004-W16, University of Oxford, Department of Economics.
- NEP-ALL-2004-07-11 (All new papers)
- NEP-CMP-2004-07-11 (Computational Economics)
- NEP-ECM-2004-07-17 (Econometrics)
- NEP-ETS-2004-07-11 (Econometric Time Series)
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