*Result*: An effective communication topology for performance optimization: a case study of the finite-volume wave modeling (FVWAM).

*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 to 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 message-passing interface (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 to 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 compare their performance in a case study using the finite-volume wave modeling (FVWAM), including both small-scale regional and large-scale global experiments. Based on the Intel MPI library, the distributed graph topology outperforms the point-to-point communication method for inter-node communication with 32 to 32 768 processes. For small-scale regional experiments with 32 to 512 processes, compared to the point-to-point method, the distributed graph topology achieved an average communication time speedup ranging from 4.78 to 11.67. For operational global wave forecasts with 1024 processes, the runtime of the FVWAM was reduced by 40.2 % when the point-to-point communication method was replaced by the distributed graph communication topology. [ABSTRACT FROM AUTHOR]

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