# PASC22 abstract

## GT4Py: High Performance Stencil Computations in Weather and Climate Applications using Python

All major weather and climate prediction models in operation today are developed in Fortran or C++, intermixing optimization directives for specific hardware architectures with numerical algorithms. The resulting codes tend to be verbose, difficult to extend and maintain, and difficult to port to new architectures. In GT4Py, a Python framework for the development of weather and climate applications, we take a different approach by separating optimization concerns from the domain scientists algorithmic development. Stencil computations are expressed using a high-level Python interface, subsequently transformed into high-performance implementations using an optimizing toolchain integrated into GT4Py. We will give an overview of the design of GT4Py, its components and the language used by scientist to express their stencil-like numerical algorithms. We further showcase a performance comparison of the FV3 dynamical core between the original Fortran implementation and a GT4Py-based application developed by a team at the Allen Institute for AI.

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