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    GPU Embedded CSE (eCSE) support

    GPU eCSE support provides funding to the UKRI research community to develop software in a sustainable manner to run on GPU-based architectures. Projects focus on developing software that facilitates research targeted at UKRI’s digital research infrastructure e.g. future Exascale supercomputing services, UK national AI services, national Tier-2 HPC services.

    Porting XCompact3D to AMD GPUs

    Very High-Order Solver Frameworks for Compressible Turbulent Mixing

    SWIFT - Facilitating performance-portable GPU acceleration in a task-based massively parallel SPH solver

    Accelerated and differentiable spherical transforms

    Developing a heterogeneous SPH solver based on the DualSPHysics GPU codes

    gpuFoam - Implementation of GPU_enablers for OpenFOAM

    Achieving high-fidelity continuum modelling on GPUs with Nektar++

    MONC GPU Acceleration

    Accelerating Gravitational Lens Modelling

    GLASS: A GPU-enabled ecosystem for simulating the universe

    GCRYSTAL - A GPU enabled CRYSTAL

    GPU Acceleration of Phonon Calculations with CASTEP

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