Parallel Computation in Econometrics: A Simplified Approach

Jurgen Doornik, Neil Shephard () and David Hendry

No 2004-W16, Economics Papers from Economics Group, Nuffield College, University of Oxford

Abstract: Parallel 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.

Keywords: Code optimization; Econometrics; High-performance computing; Matrix-programming language; Monte Carlo; MPI; Ox; Parallel computing; Random number generation. (search for similar items in EconPapers)
Pages: 32 pages
Date: 2004-01-30
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.nuff.ox.ac.uk/economics/papers/2004/w16/JADDFHNSHandbook.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nuf:econwp:0416

Access Statistics for this paper

More papers in Economics Papers from Economics Group, Nuffield College, University of Oxford Contact information at EDIRC.
Bibliographic data for series maintained by Maxine Collett ().