Multiprocessing in meteorological models [Libro electrónico] / editores: Geerd-R. Hoffmann, David F. Snelling
Hoffmann, Geerd-R [editor] | Snelling, David F [editor/a].
Tipo de material: Libro en línea Series Editor: New York, New York, United States: Springer-Verlag, c1988Descripción: xvi, 438 páginas : ilustraciones ; 25 centímetros.ISBN: 0387184570; 9783642832505 (Print); 9783642832482 (Online).Tema(s): Meteorology -- Mathematical models -- Data processing -- Congresses | Atmospheric physics -- Mathematical models -- Data processing -- Congresses | Multiprocessors -- CongressesNota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso Nota de bibliografía: Incluye bibliografía Número de sistema: 56331Contenidos:Mostrar Resumen:Tipo de ítem | Biblioteca actual | Colección | Signatura | Estado | Fecha de vencimiento | Código de barras |
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Libros | Biblioteca Electrónica Recursos en línea (RE) | Acervo General | Recurso digital | ECO400563319475 |
Incluye bibliografía
Chapter 1. Introduction: the case for multi-processing in meteorological applications.. Chapter 2. 3.-6. December 1984.. Chapter 3. 8.-11. December 1986.. Bibliography
Disponible para usuarios de ECOSUR con su clave de acceso
Numerical weather prediction on the one hand needs a very large number of floating point calculations, but on the other hand is very time-critical. Therefore, the largest computers available, i.e., the "supercomputers", have usually been acquired by the national meteorological services long before they were used in other fields of research or business. Since the available technology limits the speed of any single computer, parallel computations have become necessary to achieve further improvements in the number of results produced per time unit. This book collects the papers presented at two workshops held at ECMWF on the topic of parallel processing in meteorological models. It provides an insight into the state-of-the-art in using parallel processors operationally and allows extrapolation to other time-critical applications. It also shows trends in migrating to massive parallel systems in the near future. eng
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