Benchmark Tests for Numerical Weather Forecasts on Inexact Hardware
A reduction of computational cost would allow higher resolution in numerical weather predictions within the same budget for computation. This paper investigates two approaches that promise significant savings in computational cost: the use of reduced precision hardware, which reduces floating point...
Main Authors: | Dueben, P, Palmer, T |
---|---|
Format: | Journal article |
Language: | English |
Published: |
American Meteorological Society
2014
|
Similar Items
-
On the use of inexact, pruned hardware in atmospheric modelling.
by: Düben, P, et al.
Published: (2014) -
Machine learning emulation of gravity wave drag in numerical weather forecasting
by: Chantry, M, et al.
Published: (2021) -
WeatherBench: A Benchmark Data Set for Data‐Driven Weather Forecasting
by: Stephan Rasp, et al.
Published: (2020-11-01) -
Machine Learning Emulation of Gravity Wave Drag in Numerical Weather Forecasting
by: Matthew Chantry, et al.
Published: (2021-07-01) -
An approach to secure weather and climate models against hardware faults
by: Dueben, P, et al.
Published: (2017)