Minisymposium Presentation

The GPU4GEO project aims at developing new High-Performance Computing (HPC) tools for modelling geodynamics and ice sheet dynamics written in the Julia language. This initiative is a response to the practical demands of HPC, particularly the need for optimal performance in supercomputing environments that rely on GPU accelerators. We will present our flagship applications JustRelax.jl (geodynamics) and FastIce.jl (ice flow). These applications offer a high-level API for massively parallel thermo-mechanical Stokes solvers based on the highly-scalable pseudo-transient iterative method. We will further discuss the developed software upon which these applications are built: (i) portability to multi-GPU systems (ParallelStencil.jl and ImplicitGlobalGrid.jl); (ii) solver-agnostic material physics computations (GeoParams.j); and (iii) particles-in-cell advection (JustPIC.jl).We tackle the increasing demand for merging data-driven workflows with physics-based modelling, utilising Julia’s native support for differentiable programming. Leveraging automatic differentiation (AD), we efficiently compute model sensitivities, offering a unified framework for both inverse modelling and physics-informed machine learning. We will demonstrate Julia’s powerful AD application via Enzyme.jl for computing adjoint sensitivities in our solvers, and present benchmarks showcasing multi-GPU performance and scalability.