The Climate Modeling Alliance (CliMA) aims to build the first Earth system model that automatically learns from both Earth observations and embedded high-resolution simulations. The goal is to build a more accurate climate model with quantified uncertainties.

High computational performance on heterogeneous architectures, including CPUs, GPUs, and distributed computing architectures is essential for the project. The model is being developed in Julia to ensure portable performance at supercomputing scales for this ambitious scientific computing project.

This talk will give an overview of the project and its motivation. We will highlight how we’re pushing Julia to scale, including lessons learnt and challenges we are facing.