Presentation
P42 - A Python Dynamical Core for Operational Numerical Weather Prediction
Presenter
DescriptionNumerical weather prediction is vital for applications like population warnings and energy predictions. However, adapting forecasts to diverse hardware poses challenges. MeteoSwiss relies on the ICON model up to a one km resolution, initially ported to GPUs using OpenACC. While enabling GPU use, OpenACC+Fortran has limitations in portability and maintenance.
Exploring alternatives, we focus on the EXCLAIM project, targeting the dynamical core (55% of runtime). Implementing the dynamical core's computational stencils with gt4py Python departs from Fortran traditions. Our work details this shift, emphasizing the productivity gains with this new Python framework.
We present optimizations and compare the Python-based dynamical core with the base OpenACC version, highlighting computational efficiency and development ease. Acknowledging challenges, especially in operational weather prediction.
Exploring alternatives, we focus on the EXCLAIM project, targeting the dynamical core (55% of runtime). Implementing the dynamical core's computational stencils with gt4py Python departs from Fortran traditions. Our work details this shift, emphasizing the productivity gains with this new Python framework.
We present optimizations and compare the Python-based dynamical core with the base OpenACC version, highlighting computational efficiency and development ease. Acknowledging challenges, especially in operational weather prediction.
TimeTuesday, June 49:56 - 9:57 CEST
LocationHG F 30 Audi Max
Session Chair
Event Type
Poster
Authors
