HPC numerical codes have been largely developed using Fortran or C due to their speed. More accessible languages, like Matlab or Python have found little use for such codes due to their poorer performance. Julia offers both, speed and accessibility for serial calculations and on small clusters. But how a Julia/MPI code scales on large HPC facilities has not been tested yet.

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Using the Julia code Trixi.jl we test if Julia scales well on large HPC clusters. Trixi.jl uses the MPI library for parallelization and is well suited for this test. Using resources from the Jülich Supercomputing Centre we run simulations on up to 61,440 MPI ranks on 480 compute nodes for a Taylor-Green vortex

problem in three dimensions. We compare the results with the Fortran code FLUXO and see that Trixi.jl scales well for all used MPI ranks and outperforms FLUXO.

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