Accelerating Geostatistical Modeling and Prediction With Mixed-Precision Computations: A High-Productivity Approach With PaRSEC

Geostatistical modeling, one of the prime motivating applications for exascale computing, is a technique for predicting desired quantities from geographically distributed data, based on statistical models and optimization of parameters. Spatial data are assumed to possess properties of stationarity...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems 2022-04, Vol.33 (4), p.964-976
Hauptverfasser:	Abdulah, Sameh, Cao, Qinglei, Pei, Yu, Bosilca, George, Dongarra, Jack, Genton, Marc G., Keyes, David E., Ltaief, Hatem, Sun, Ying
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Cholesky factorization Climate/weather prediction Computational modeling Computer Science Covariance matrices Covariance matrix Data models Data structures Distributed memory dynamic runtime systems Engineering Geographical distribution geospatial statistics Geostatistics high performance computing Maximum likelihood estimation multiple precisions Nodes Optimization Predictive models Run time (computers) Runtime Spatial data Statistical models Task analysis user-productivity
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