An Effective Communication Topology for Performance Optimization: A Case Study of the Finite Volume WAve Modeling (FVWAM)

Abstract. High-resolution models are essential for simulating small-scale processes and topographical features, which play a crucial role in understanding meteorological and oceanic events, as well as climatic patterns. High-resolution modeling requires substantial improvement on the parallel scalability of the model to reduce runtime, while massive parallelism is associated with intensive communications. Point-to-point communication is extensively utilized for neighborhood communication in earth models due to its flexibility. The distributed graph topology, first introduced in the MPI version 2.2, provides a scalable and informative communication method. It has demonstrated significant speedups over the point-to-point communication method based on a variety of synthetic and real-world communication graph datasets. But its application in earth models for neighborhood communication is rarely studied. In this study, we implemented neighborhood communication using both the traditional point-to-point communication method and the distributed graph communication topology. We then compared their performance in a case study of the Finite Volume WAve Modeling (FVWAM). Across all tests with 512 to 32,768 processes, the communication time speedup of the distributed graph communication topology ranged from 1.28 to 5.63 compared to the point-to-point communication method. For operational global wave forecasts with 1,024 processes, the runtime of the FVWAM reduced 40.2 % when the point-to-point communication method was replaced by the distributed graph communication topology.