Abstract
Under the joint influence of high-intensity human activities and climate change, the coastal ecological environment is deteriorating, and the ecological environment security and the sustainable development of the marine economy are seriously threatened. Therefore, it is of great significance to establish a high-resolution ecological environment operational forecasting system. To meet the run time requirements of the ecological operational forecasting system, a variety of parallel optimization methods were proposed to improve the operation efficiency of the model. First, based on the National Marine Environmental Forecasting Center's Lenovo cluster, the ROMS benchmark experiment was expanded to the 4000 Processes scale. A good speedup was obtained by the experiment. The ROMS model was analysed with strong scalability. Second, in the hydrodynamic-ecological simulation experiment of the Bohai Sea - Yellow Sea - East China Sea, by optimizing Vector, InfiniBand, and Parallel I/O, the performance of the model can be improved by 270% while maintaining the same computing resources. That computing resources were more reasonably used lay the foundation for the operational forecast.
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Acknowledgment
This research is supported by the National Natural Science Foundation of China (41976200), the project of Guangdong Ocean University (060302032106) and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (SML2022SP301). We acknowledge the comments of anonymous reviewers.
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Wang, Y., Zheng, J., Zhang, T., Liang, P., Lin, B. (2023). Data Analyses and Parallel Optimization of the Regional Marine Ecological Model. In: Yu, Z., et al. Data Science. ICPCSEE 2023. Communications in Computer and Information Science, vol 1880. Springer, Singapore. https://doi.org/10.1007/978-981-99-5971-6_16
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DOI: https://doi.org/10.1007/978-981-99-5971-6_16
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