Development and performance optimization of a parallel computing infrastructure for an unstructured-mesh modelling framework
- 1Ministry of Education Key Laboratory for Earth System Modeling, and Department of Earth System Science, Tsinghua University, Beijing, 100084, China
- 2Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China
- 3National Supercomputing Center in Wuxi, Wuxi, 214071, China
- 4State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, 100081, China
- 1Ministry of Education Key Laboratory for Earth System Modeling, and Department of Earth System Science, Tsinghua University, Beijing, 100084, China
- 2Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China
- 3National Supercomputing Center in Wuxi, Wuxi, 214071, China
- 4State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, 100081, China
Abstract. This paper describes the development and performance optimization of a parallel computing infrastructure for an unstructured-mesh global model (GRIST; Global-to-Regional Integrated forecast SysTem). The focus is on three major aspects that facilitate rapid iterative development, including parallel computing, index optimization and an efficient group I/O strategy. For parallel computing, the METIS tool is used for the partition of the global mesh, which is flexible and convenient for both the quasi-uniform and variable-resolution simulations. The scaling tests show that the partition method is efficient. To improve the cache efficiency, several mesh index reordering strategies are investigated to optimize the performance of the indirect addressing scheme used in the stencil calculations. The numerical results show that the indexing strategies are able to speed up the calculations, especially for running with a small number of processes. To overcome the bottleneck of poor I/O efficiency for the high-resolution or massively parallel simulations, a group parallel I/O method is implemented and proven to be of high efficiency in the numerical experiments. Altogether, these three aspects of the parallel computing toolkits are encapsulated in a few interfaces, which can be used for general parallel modelling on unstructured meshes.
Zhuang Liu et al.


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RC1: 'Review of Development and performance optimization of a parallel computing infrastructure for an unstructured-mesh modelling framework', Anonymous Referee #1, 23 Oct 2020
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AC1: 'Responses to the comments of referee #1', Xiaomeng Huang, 01 Dec 2020
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AC1: 'Responses to the comments of referee #1', Xiaomeng Huang, 01 Dec 2020
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RC2: 'Referee comments', Anonymous Referee #2, 27 Oct 2020
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AC2: 'Responses to the comments of referee #2', Xiaomeng Huang, 01 Dec 2020
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AC2: 'Responses to the comments of referee #2', Xiaomeng Huang, 01 Dec 2020
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SC1: 'executive editor comment on gmd-2020-158', Astrid Kerkweg, 27 Oct 2020
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AC3: 'Responses to the comments of the executive editor', Xiaomeng Huang, 01 Dec 2020
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AC3: 'Responses to the comments of the executive editor', Xiaomeng Huang, 01 Dec 2020


-
RC1: 'Review of Development and performance optimization of a parallel computing infrastructure for an unstructured-mesh modelling framework', Anonymous Referee #1, 23 Oct 2020
-
AC1: 'Responses to the comments of referee #1', Xiaomeng Huang, 01 Dec 2020
-
AC1: 'Responses to the comments of referee #1', Xiaomeng Huang, 01 Dec 2020
-
RC2: 'Referee comments', Anonymous Referee #2, 27 Oct 2020
-
AC2: 'Responses to the comments of referee #2', Xiaomeng Huang, 01 Dec 2020
-
AC2: 'Responses to the comments of referee #2', Xiaomeng Huang, 01 Dec 2020
-
SC1: 'executive editor comment on gmd-2020-158', Astrid Kerkweg, 27 Oct 2020
-
AC3: 'Responses to the comments of the executive editor', Xiaomeng Huang, 01 Dec 2020
-
AC3: 'Responses to the comments of the executive editor', Xiaomeng Huang, 01 Dec 2020
Zhuang Liu et al.
Zhuang Liu et al.
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