High Performance Multivariate Geospatial Statistics on Manycore Systems

Modeling and inferring spatial relationships and predicting missing values of environmental data are some of the main tasks of geospatial statisticians. These routine tasks are accomplished using multivariate geospatial models and the cokriging technique. The latter requires the evaluation of the ex...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems 2021-11, Vol.32 (11), p.2719-2733
Hauptverfasser:	Salvana, Mary Lai O., Abdulah, Sameh, Huang, Huang, Ltaief, Hatem, Sun, Ying, Genton, Marc G., Keyes, David E.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Approximation Computational modeling Concurrency Data collection Datasets Gaussian log-likelihood Geospatial analysis geospatial statistics Graphics processing units high-performance computing large multivariate spatial data low-rank approximation Mathematical model Mathematical models Meteorology Multivariate analysis multivariate modeling/prediction Numerical models Parameter estimation Predictive models Robustness (mathematics) Schedules Task scheduling
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