ACCESS Technical Landscape Assessment: High-Performance Computing, Data, and Machine-Learning

High Performance Computing (HPC), data and machine learning (ML) capabilities are rapidly evolving, presenting both opportunities and challenges for climate and weather modelling. These challenges have significant implications for the Australian Community Climate and Earth System Simulator (ACCESS) and the broader research community that relies on ACCESS data outputs. As a national research infrastructure, ACCESS-NRI will play a critical role in supporting the community through this transition and ensuring Australia’s climate modelling capability remains scalable, resilient and internationally competitive.   

This document provides an assessment of the current technical landscape and examines how emerging developments in HPC, data practices, and ML may affect the future of ACCESS. It outlines key trends and pressures across these areas, highlighting where future work will be required to maintain scientific impact and stay at the cutting edge of weather and climate modelling.