Towards exascale simulations of granular fluidization in offshore wind turbine foundations
Kemmler S, Artinov A, Cuéllar P, Köstler H (2026)
Publication Type: Journal article
Publication year: 2026
Journal
DOI: 10.1177/10943420261441738
Abstract
Fully-resolved micromechanical simulations coupling the Lattice Boltzmann Method (LBM) with the Discrete Element Method (DEM) provide high-fidelity insights into granular fluidization. However, the substantial computational demands of such simulations require efficient implementations on supercomputing architectures. This work presents a comprehensive performance analysis of a fully-resolved LBM-DEM model to study granular fluidization, i.e., piping erosion, during the installation of an offshore caisson foundation. The performance evaluation focuses on real-world workloads rather than simplified benchmark problems to obtain realistic performance insights. The study considers a diverse range of state-of-the-art HPC hardware architectures, namely the LUMI and MareNostrum 5 EuroHPC supercomputers, both CPU and GPU partitions. The results demonstrate that GPU-based systems generally outperform the CPU-based systems. Strong and weak scaling analyses were conducted with up to 512 nodes, and parallel efficiencies reached up to 92%. Nonetheless, the results also indicate that atomic add operations on GPUs can become a bottleneck for the parallel efficiency at large scales. Moreover, the study reveals a close link between physical variations of the setup and significant scaling implications, underscoring the need to consider physical model characteristics in scaling assessments.
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Germany (DE)How to cite
APA:
Kemmler, S., Artinov, A., Cuéllar, P., & Köstler, H. (2026). Towards exascale simulations of granular fluidization in offshore wind turbine foundations. International Journal of High Performance Computing Applications. https://doi.org/10.1177/10943420261441738
MLA:
Kemmler, Samuel, et al. "Towards exascale simulations of granular fluidization in offshore wind turbine foundations." International Journal of High Performance Computing Applications (2026).
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