Using the Parallel Virtual Machine for Everyday Analysis

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dc.creatorNoble, M. S.
dc.creatorHouck, J. C.
dc.creatorDavis, J. E.
dc.creatorYoung, A.
dc.creatorNowak, M.
dc.date2005-10-24
dc.date.accessioned2026-07-07T06:44:00Z
dc.date.available2026-07-07T06:44:00Z
dc.descriptionA review of the literature reveals that while parallel computing is sometimes employed by astronomers for custom, large-scale calculations, no package fosters the routine application of parallel methods to standard problems in astronomical data analysis. This paper describes our attempt to close that gap by wrapping the Parallel Virtual Machine (PVM) as a scriptable S-Lang module. Using PVM within ISIS, the Interactive Spectral Interpretation System, we've distributed a number of representive calculations over a network of 25+ CPUs to achieve dramatic reductions in execution times. We discuss how the approach applies to a wide class of modeling problems, outline our efforts to make it more transparent for common use, and note its growing importance in the context of the large, multi-wavelength datasets used in modern analysis.
dc.description4 pages; manuscript for oral presentation given at ADASS XV, Madrid
dc.identifierhttps://arxiv.org/abs/astro-ph/0510688
dc.identifierhttp://arxiv.org/abs/astro-ph/0510688
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/102628
dc.subjectAstrophysics
dc.subjectDistributed, Parallel, and Cluster Computing
dc.titleUsing the Parallel Virtual Machine for Everyday Analysis
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