Reduced-precision parametrization: lessons from an intermediate-complexity atmospheric model
Reducing numerical precision can save computational costs which can then be reinvested for more useful purposes. This study considers the effects of reducing precision in the parametrizations of an intermediate complexity atmospheric model (SPEEDY). We find that the difference between double-precisi...
| Автори: | , , , |
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| Формат: | Journal article |
| Мова: | English |
| Опубліковано: |
Wiley
2020
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