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| Format: | Preprint |
| Veröffentlicht: |
2023
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| Online-Zugang: | https://arxiv.org/abs/2308.06605 |
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| _version_ | 1866914624001015808 |
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| author | 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 A. E. Luo, Shirui Koric, Seid Zheng, Weimin |
| author_facet | 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 A. E. Luo, Shirui Koric, Seid Zheng, Weimin |
| contents | 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, which involves a time-dependent simulation of a complete engine, incorporating all the aerodynamic and heat transfer components. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_06605 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Towards Exascale Computation for Turbomachinery Flows 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 A. E. Luo, Shirui Koric, Seid Zheng, Weimin Distributed, Parallel, and Cluster Computing 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, which involves a time-dependent simulation of a complete engine, incorporating all the aerodynamic and heat transfer components. |
| title | Towards Exascale Computation for Turbomachinery Flows |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2308.06605 |