Parallel Computing Applied to Satellite Images Processing for Solar Resource Estimates

dc.creatorAlonso Suárez,Rodrigo
dc.creatorNesmachnow,Sergio
dc.date2012-12-01
dc.date.accessioned2023-09-25T18:35:14Z
dc.date.available2023-09-25T18:35:14Z
dc.identifierhttp://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002012000300005
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8838437
dc.descriptionThis article presents the application of parallel computing techniques to process satellite imagery information for solar resource estimates. A distributed memory parallel algorithm is introduced, which is capable to generate the required inputs from visible channel images to feed a statistical solar irradiation model. The parallelization strategy consists in distributing the images within the available processors, and so, every image is accessed only by one process. The experimental analysis demonstrate that a maximum speedup value of 2.32 is achieved when using four computing resources, but beyond that point the performance rather decrease due to hard-disk input/output velocity.
dc.formattext/html
dc.languageen
dc.publisherCentro Latinoamericano de Estudios en Informática
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceCLEI Electronic Journal v.15 n.3 2012
dc.subjectparallel computing
dc.subjectsatellite images
dc.subjectsolar resource assessment
dc.titleParallel Computing Applied to Satellite Images Processing for Solar Resource Estimates
dc.typeinfo:eu-repo/semantics/article


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