swNEMO_v4.0: an ocean model NEMO for the next generation Sunway supercomputer
Yuejin Ye, Zhenya Song, Shengchang Zhou, Yao Liu, Qi Shu, Bingzhuo Wang, Weiguo Liu, Fangli Qiao, Lanning Wang · Geoscientific Model Development Discussions · 2022
Abstract. The current large-scale parallel barrier of ocean general circulation models (OGCMs) makes it difficult to meet the computing demand of high resolution. Fully considering both the computational characteristics of OGCMs and the heterogeneous many-core architecture of the new Sunway supercomputer, swNEMO_v4.0, with ultrahigh scalability is developed. Three innovations and breakthroughs are shown in our work: (1) A highly adaptive, efficient four-level parallelization framework for OGCMs is proposed to release a new level of parallelism along the compute-dependency column dimension. (2) A many-core optimization method using blocking by remote memory access (RMA) and a dynamic cache scheduling strategy, effectively utilizing the temporal and spatial locality of data. The test shows that the actual DMA bandwidth is greater than 90 % of the ideal bandwidth after optimization, and the maximum is up to 95 %. (3) A mixed-precision optimization method with half-, single-, and double-precision is explored, which can effectively improve the computation performance, while maintaining the simulated accuracy of OGCMs. The results demonstrate that swNEMO_v4.0 has ultrahigh scalability, achieving up to 99.29 % parallel efficiency with a resolution of 500 m using 27,988,480 cores, reaching the peak performance with 1.97 PFlops.