Together with the University of Hamburg, ACES aims to reduce data volume below 10% of the original data with no recognizable impact on the scientific quality.
Splitting science code from the nitty gritty details of exploiting parallelism on specific computer architectures using DSLs for weather and climate : PSyclone and the new LFRic Weather and Climate Model.
ACES involvement in ESIWACE includes developing new I/O sub-systems capable of handling pre-exascale data flows both at simulation time, and in the analysis environment.
Managing and analysing petascale data requires dedicated computing systems with a specialised software environment. ACES will be working on understanding real scientific workflows and how best to deploy such hardware and software infrastructure.
Containerisation shows enormous potential for both simulation and analysis workflows. This project encompasses a range of mini-app tests of the applicability of containers for existing HPC workflows.
Managing large scale data systems requires metadata systems to match.