Regional Ocean Model Parallel Optimization in “Sunway TaihuLight”

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.