29054

Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core

Robert Jendersie, Christian Lessig, Thomas Richter
Institute for Simulation and Graphics, Institute of Analysis und Numerics, Otto-von-Guericke, University Magdeburg, Germany
arXiv:2402.00466 [cs.DC], (1 Feb 2024)

@misc{jendersie2024gpuparallelization,

   title={Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core},

   author={Robert Jendersie and Christian Lessig and Thomas Richter},

   year={2024},

   eprint={2402.00466},

   archivePrefix={arXiv},

   primaryClass={cs.DC}

}

The cryosphere plays a significant role in Earth’s climate system. Therefore, an accurate simulation of sea ice is of great importance to improve climate projections. To enable higher resolution simulations, graphics processing units (GPUs) have become increasingly attractive as they offer higher floating point peak performance and better energy efficiency compared to CPUs. However, making use of the theoretical peak performance usually requires more care and effort in the implementation. In recent years, a number of frameworks have become available that promise to simplify general purpose GPU programming. In this work, we compare multiple such frameworks, including CUDA, SYCL, Kokkos and PyTorch, for the parallelization of neXtSIM, a finite-element based dynamical core for sea ice. We evaluate the different approaches according to their usability and performance.
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