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On the performance, scalability and sensitivity analysis of a large air pollution model

dc.creatorVassil Nikolov Alexandrov
dc.date2016
dc.date.accessioned2018-10-18T22:08:21Z
dc.date.available2018-10-18T22:08:21Z
dc.identifier.issn18770509
dc.identifier.doi10.1016/j.procs.2016.05.525
dc.identifier.urihttp://hdl.handle.net/11285/630563
dc.descriptionComputationally efficient sensitivity analysis of a large-scale air pollution model is an important issue we focus on in this paper. Sensitivity studies play an important role for reliability analysis of the results of complex nonlinear models as those used in the air pollution modelling. There is a number of uncertainties in the input data sets, as well as in some internal coefficients, which determine the speed of the main chemical reactions in the chemical part of the model. These uncertainties are subject to our quantitative sensitivity study. Monte Carlo and quasi-Monte Carlo algorithms are used in this study. A large number of numerical experiments with some special modifications of the model must be carried out in order to collect the necessary input data for the particular sensitivity study. For this purpose we created an efficient high performance implementation SA-DEM, based on the MPI version of the package UNI-DEM. A large number of numerical experiments were carried out with SA-DEM on the IBM MareNostrum III at BSC - Barcelona, helped us to identify a severe performance problem with an earlier version of the code and to resolve it successfuly. The improved implementation appears to be quite efficient for that challenging computational problem, as our experiments show. Some numerical results with performance and scalability analysis of these results are presented in the paper. © The Authors. Published by Elsevier B.V.
dc.languageeng
dc.publisherElsevier B.V.
dc.relationhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84978485760&doi=10.1016%2fj.procs.2016.05.525&partnerID=40&md5=fbf362777ed75a15cee0d958abc25033
dc.relationInvestigadores
dc.relationEstudiantes
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceProcedia Computer Science
dc.subjectAir pollution
dc.subjectChemical analysis
dc.subjectInput output programs
dc.subjectMonte Carlo methods
dc.subjectNumerical methods
dc.subjectParallel algorithms
dc.subjectPollution
dc.subjectReliability analysis
dc.subjectScalability
dc.subjectSupercomputers
dc.subjectAir Pollution Modeling
dc.subjectComputationally efficient
dc.subjectHigh performance implementations
dc.subjectLarge scale air pollution
dc.subjectMonte carlo and quasi-monte carlo algorithms
dc.subjectPerformance
dc.subjectPerformance and scalabilities
dc.subjectSpeed up
dc.subjectSensitivity analysis
dc.subject.classification7 INGENIERÍA Y TECNOLOGÍA
dc.titleOn the performance, scalability and sensitivity analysis of a large air pollution model
dc.typeConferencia
dc.identifier.volume80
dc.identifier.startpage2053
dc.identifier.endpage2061
refterms.dateFOA2018-10-18T22:08:21Z


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