Multiprocessing meteorological models de hoffmann geerd (14 resultados)

Condición: New.

Condición: New. In English.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Condición: New. pp. xvi + 483.

Paperback. Condición: Brand New. reprint edition. 454 pages. 9.50x6.80x1.00 inches. In Stock.

Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Hardcover. Condición: Good. Dust Jacket NOT present. CD WILL BE MISSING. . SHIPS FROM MULTIPLE LOCATIONS. book.

Condición: new. Questo è un articolo print on demand.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 460 pp. Englisch.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 nat.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 460 pp. Englisch.…

Condición: New. Print on Demand pp. xvi + 483 106 Figures.

Condición: New. PRINT ON DEMAND pp. xvi + 483.