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    吴琦, 倪裕芳, 黄小猛. 基于“神威·太湖之光”的区域海洋模式并行优化[J]. 计算机研究与发展, 2019, 56(7): 1556-1566. DOI: 10.7544/issn1000-1239.2019.20180791
    引用本文: 吴琦, 倪裕芳, 黄小猛. 基于“神威·太湖之光”的区域海洋模式并行优化[J]. 计算机研究与发展, 2019, 56(7): 1556-1566. DOI: 10.7544/issn1000-1239.2019.20180791
    Wu Qi, Ni Yufang, Huang Xiaomeng. Regional Ocean Model Parallel Optimization in “Sunway TaihuLight”[J]. Journal of Computer Research and Development, 2019, 56(7): 1556-1566. DOI: 10.7544/issn1000-1239.2019.20180791
    Citation: Wu Qi, Ni Yufang, Huang Xiaomeng. Regional Ocean Model Parallel Optimization in “Sunway TaihuLight”[J]. Journal of Computer Research and Development, 2019, 56(7): 1556-1566. DOI: 10.7544/issn1000-1239.2019.20180791

    基于“神威·太湖之光”的区域海洋模式并行优化

    Regional Ocean Model Parallel Optimization in “Sunway TaihuLight”

    • 摘要: 海洋模式作为地球数值模拟中重要的组成模块,在很多领域都起到了至关重要的作用,不仅是研究海洋、河口和海岸不可或缺的科研手段,基于海洋模式搭建的预报系统还能够实时预测台风、海啸等现象.为了模拟更细粒度的海洋变化,海洋模式朝着更高的分辨率和更多的物理参数化方案发展,一般的计算机已无法满足其需求.随着散热和功耗成为通用处理器的主要瓶颈,多核、众核以及由此导致的异构已成为下一代超级计算机的发展趋势,这也为发展高分辨率海洋模式提供了坚实的基础平台.基于国产超级计算机“神威·太湖之光”,利用其异构众核体系结构的优势对普林斯顿海洋模式(Princeton ocean model, POM)进行移植和优化,从而充分发挥了国产异构众核平台的特点和优势.基于神威的高分辨率海洋模式swPOM(Sunway Princeton ocean model)在主从核协作下运行效率达到纯主核的13倍,是通用Intel平台的2.8倍左右,可扩展到25万核上运行,为实时预报系统提供了保障.

       

      Abstract: As an important component of earth system modeling, the ocean model plays a vital role in many fields. It is not only an indispensable scientific research method for studying oceans, estuaries and coasts, but also the forecasting system based on the ocean model can predict typhoons and tsunami in real time. In order to simulate more fine-grained oceanic changes, the ocean model is moving toward higher resolution and more physical parameterization schemes, and general computers are no longer able to meet their needs. As heat dissipation and power consumption become the major bottlenecks of general-purpose processors, multi-core, many cores, and the resulting heterogeneous platform has become the main trend of next generation of supercomputers, which provides a solid foundation for developing high-resolution ocean models. Based on the domestic supercomputer “Sunway TaihuLight”, this paper takes the advantages of its heterogeneous many-core architecture to transplant and optimize the regional ocean model: Princeton ocean model (POM), and fully utilizes the characteristics and advantages of the domestic heterogeneous many-core platform. By using master-slave core collaboration, the high-resolution ocean model swPOM increases the performance efficiency by about 13 times compared with the pure master core and about 2.8 times compared with the general Intel platform, and can scale up to 250 000 cores to provide sufficient support for real-time forecasting system.

       

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