Minisymposium Presentation

High-order discontinuous Galerkin (DG) methods offer the same level of accuracy as traditional methods while using fewer degrees of freedom. At the same time, their increase in arithmetic complexity occurs locally, leading to efficient algorithms with good scalability and throughput, even on modern GPUs. In this talk we present our current efforts in developing a novel, exascale-ready dynamical core for weather and climate simulations, in which a DG scheme provides increased accuracy and performance and supports efficient utilization of next generation supercomputing hardware. Our approach is based on the flow solver Trixi.jl, which is built around a state-of-the-art spectral element method with entropy conserving flux differencing for improved robustness and with adaptive mesh refinement for reduced time-to-solution. Written in the modern high level language Julia, Trixi.jl provides rapid prototyping capabilities, HPC-grade scalability, and vendor-agnostic GPU support. Legacy applications can utilize our methods via our interface library libtrixi, which provides APIs in C and Fortran. We will present results of simulations steered by the Fortran code MESSy and show performance analyses of our CPU and GPU codes.