English

Towards Exascale for Wind Energy Simulations

Computational Engineering, Finance, and Science 2022-10-04 v1 Distributed, Parallel, and Cluster Computing Performance

Abstract

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer (ABL) flows that are of direct relevance to wind energy production. The first is NekRS, a high-order, unstructured-grid, spectral element code. The second, AMR-Wind, is a block-structured, second-order finite-volume code with adaptive-mesh-refinement capabilities. The objective of this study is to co-develop these codes in order to improve model fidelity and performance for each. These features will be critical for running ABL-based applications such as wind farm analysis on advanced computing architectures. To this end, we investigate the performance of NekRS and AMR-Wind on the Oak Ridge Leadership Facility supercomputers Summit, using 4 to 800 nodes (24 to 4,800 NVIDIA V100 GPUs), and Crusher, the testbed for the Frontier exascale system using 18 to 384 Graphics Compute Dies on AMD MI250X GPUs. We compare strong- and weak-scaling capabilities, linear solver performance, and time to solution. We also identify leading inhibitors to parallel scaling.

Keywords

Cite

@article{arxiv.2210.00904,
  title  = {Towards Exascale for Wind Energy Simulations},
  author = {Misun Min and Michael Brazell and Ananias Tomboulides and Matthew Churchfield and Paul Fischer and Michael Sprague},
  journal= {arXiv preprint arXiv:2210.00904},
  year   = {2022}
}

Comments

13 pages, 7 figures, 6 tables

R2 v1 2026-06-28T02:36:16.157Z