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Key Exploitable Results (KERs)

Within ESiWACE3, Key Exploitable Results (KERs) include a portfolio of software tools, model codes, and applications developed to advance performance assessment and optimisation for Earth system modelling. These results support researchers and practitioners in analysing computational efficiency, testing scalability, and improving portability across emerging HPC architectures.

This section highlights these KERs and the results they generate, showcasing practical solutions built around realistic climate and weather workloads. By focusing on representative scientific use cases rather than synthetic metrics such as High Performance Linpack (HPL), they provide actionable insight into how computing systems perform for real modelling and forecasting applications.

  • R1 - HPCW

    HPC Weather benchmarking suite. HPCW isolates key elements in the workflow of weather and climate prediction systems to improve performance and to allow a detailed performance comparison for different hardware platforms thus fostering co-design with vendors and technology providers
    Show More -R1 - HPCW

  • R2- AUTO-RPE

    Tools to reduce the precision of the variable model automatically from double to single
    Show More -R2- AUTO-RPE

  • RP3- Automatic Performance Profiling (APP)

    Tools to analise the computational performance of an application automaticaly
    Show More -RP3- Automatic Performance Profiling (APP)

  • R25- Docker EC-EARTH

    Containerization of the code EC-EARTH for running climate simulation (comes from AUTOSUBMIT WF manager and EC-EARTH)
    Show More -R25- Docker EC-EARTH

  • R6- NEMO on GPU

    porting / integration on MN5 and LUMI
    Show More -R6- NEMO on GPU

  • R11-FDO4Climate: Initial Evaluation

    Evaluation of the readiness of published climate simulation output for automated anaysis. High potential because automated analysability of climate data has not been evaluate before and because specifications to enhance/enable machine actionability can be deduced from this work
    Show More -R11-FDO4Climate: Initial Evaluation

  • R13-Field Compression Library

    The Field Compression Library can be used by scientific groups to explore data compression for weather and climate science
    Show More -R13-Field Compression Library

  • R8- PSyclone

    Use of PSyclone in the NEMO build system. PSyclone is also used by the official NEMO release and it is part of the NEMO build system.
    Show More -R8- PSyclone

  • R14-FVM

    This is the new dynamical core of ECMWF that will be used for operational weather predictions and climate simulations. The model has been developed outside of ESiWACE but ESiWACE is supporting the porting of the dycore to GPU hardware and heteoregeneous hardware via the GT4Py DSL
    Show More -R14-FVM

  • R24-Containerization of EC-Earth

    Containerisation is one potential approach to port EC-Earth to new systems, which includes pre-exascale systems. Given that access to tier 0 systems usually comes with severe time constraints and strong focus on actual production runs, container based porting can help to better utilise the assigned resources.
    Show More -R24-Containerization of EC-Earth

  • R27- Compression-Hackathon

    The application of data compression online as a simple toy model (Lorenz96) is running was explored. Results of the ESiW3 hackathon October 2023.
    Show More -R27- Compression-Hackathon

  • R30-Online Laboratory for Climate Science and Meteorology

    The Online Laboratory for Climate Science and Meteorology provides a JupyterLab-like environment that has common climate and meteorology packages and libraries preinstalled. Provides researchers an installation-free quick-to-launch Jupyter environment in their web browser (runs entirely inside the user’s webbrowser using WebAssembly) that can be used for running small exper.
    Show More -R30-Online Laboratory for Climate Science and Meteorology

  • R31- Compression Laboratory

    The (field) compression laboratory builds on ECMWF’s field compression library. It provides several Jupyter notebooks that explore data compression for weather and climate data. The notebooks can be run locally or in the Online Laboratory (R30) (https://compression.lab.climet.eu).
    Show More -R31- Compression Laboratory

  • R32-Kernel Tuner Ecosystem

    The Kernel Tuner Ecosystem is a set of tools and libraries to improve the perfrormance of GPU software.
    Show More -R32-Kernel Tuner Ecosystem