66 research outputs found
Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core
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 this theoretical peak performance, which is based on massive data
parallelism, 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.Comment: revision for PASC 202
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