Please use this identifier to cite or link to this item: https://doi.org/10.1364/AO.44.007125
DC FieldValue
dc.titleTemporal fringe pattern analysis with parallel computing
dc.contributor.authorNg, T.W.
dc.contributor.authorAng, K.T.
dc.contributor.authorArgentini, G.
dc.date.accessioned2014-06-18T05:09:35Z
dc.date.available2014-06-18T05:09:35Z
dc.date.issued2005-11-20
dc.identifier.citationNg, T.W., Ang, K.T., Argentini, G. (2005-11-20). Temporal fringe pattern analysis with parallel computing. Applied Optics 44 (33) : 7125-7129. ScholarBank@NUS Repository. https://doi.org/10.1364/AO.44.007125
dc.identifier.issn00036935
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/67808
dc.description.abstractTemporal fringe pattern analysis is invaluable in transient phenomena studies but necessitates long processing times. Here we describe a parallel computing strategy based on the single-program multiple-data model and hyperthreading processor technology to reduce the execution time. In a two-node cluster workstation configuration we found that execution periods were reduced by 1.6 times when four virtual processors were used. To allow even lower execution times with an increasing number of processors, the time allocated for data transfer, data read, and waiting should be minimized. Parallel computing is found here to present a feasible approach to reduce execution times in temporal fringe pattern analysis. © 2005 Optical Society of America.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1364/AO.44.007125
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentBACHELOR OF TECHNOLOGY PROGRAMME
dc.description.doi10.1364/AO.44.007125
dc.description.sourcetitleApplied Optics
dc.description.volume44
dc.description.issue33
dc.description.page7125-7129
dc.description.codenAPOPA
dc.identifier.isiut000233345000015
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