Optimization of Parallel Fourier Transform in YHGSM Based on Computation–Communication Overlap
Yuntian Zheng, Jianping Wu, Tun Chen, Jinhui Yang, Fukang Yin, Xinyu Chen · Electronics · 2025
Spectral models, due to their stability and efficiency, have become one of the most popular approaches for implementing numerical weather prediction systems. Given the complexity of these models, they often require the use of multi-node computing resources for parallel processing to meet the stringent real-time requirements. However, as the number of nodes increases, the efficiency of inter-node communication becomes a critical bottleneck. In the case of the Yin-He Global Spectral Model (YHGSM), developed by the National University of Defense Technology, communication overhead is very high during the Fourier transform section, which consists of the transform itself and the subsequent transposition from the z-μ decomposition to the z-m decomposition. To address this challenge, we introduce an optimized scheme that overlaps communication with computation. By grouping corresponding communication and computation tasks, this approach leverages non-blocking communication techniques within MPI, combined with the use of asynchronous communication progress threads. Our experimental results demonstrate that this scheme can reduce execution time by up to 30% compared to the non-overlapped version, thereby significantly hiding communication overhead and enhancing the efficiency of YHGSM.