Abstract: GRAPES(Global and Regional Assimilation and Prediction System) is a new generation of numerical weather prediction(NWP) system of China. As the system processes amount of data and requires high real-time, it is always a hot research field of parallel computing. This is the first time that we use GPU(Graphics Processor Unit) general-pur-pose computing and CUDA technology on RRTM(Rapid Radiative transfer model) long-wave radiation module of GRAPES Meso model for parallel processing. Based on the analysis of computing performance, and according to the characteristics of the GPU architecture, the RRTM module parallel computational efficiency was optimized from the aspect of code tuning,memory,compiler options and etc. The optimization results indicate that the performance obtains a speedup of 14.3 X.Experiments were carried out on the GPU platform. The results show that the parallel computing algorithm is correct, stable and efficient for operational implementation of GRAPES in near future.

Key words: GPU, CUDA, GRAPES system, RRTM, Parallel computing