Details

Autor(en) / Beteiligte

• Fu, Yuhang
• Shen, Weiqi
• Cui, Jiahuan
• Zheng, Yao
• Yang, Guangwen
• Liu, Zhao
• Zhang, Jifa
• Ji, Tingwei
• Xie, Fangfang
• Lv, Xiaojing
• Liu, Hanyue
• Liu, Xu
• Liu, Xiyang
• Song, Xiaoyu
• Tao, Guocheng
• Yan, Yan
• Tucker, Paul
• Miller, Steven
• Luo, Shirui
• Koric, Seid
• Zheng, Weimin

Titel

Toward Exascale Computation for Turbomachinery Flows

Ist Teil von

• Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2023, p.1-12

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2023

Quelle

ACM Digital Library

Beschreibungen/Notizen

• A state-of-the-art large eddy simulation code has been developed to solve compressible flows in turbomachinery. The code has been engineered with a high degree of scalability, enabling it to effectively leverage the many-core architecture of the new Sunway system. A consistent performance of 115.8 DP-PFLOPs has been achieved on a high-pressure turbine cascade consisting of over 1.69 billion mesh elements and 865 billion Degree of Freedoms (DOFs). By leveraging a high-order unstructured solver and its portability to large heterogeneous parallel systems, we have progressed towards solving the grand challenge problem outlined by NASA [1], which involves a time-dependent simulation of a complete engine, incorporating all the aerodynamic and heat transfer components.