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CC-RRTMG_SW++: Further optimizing a shortwave radiative transfer scheme on GPU

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Abstract

Atmospheric radiation is one of the most important atmospheric physics, and its expensive computation cost severely restricts the numerical simulation of atmospheric general circulation models. Therefore, it is necessary to study an efficient radiation parameterization scheme. Due to the powerful computing power of GPU, more and more numerical models are being transplanted to GPU. The CUDA C version (CC-RRTMG_SW) of the rapid radiative transfer model for general circulation models (RRTMG) shortwave radiation scheme (RRTMG_SW) has successfully run on GPU, but its computing efficiency is not yet very high, and the performance potential of GPU computing needs to be realized further. This paper is dedicated to optimizing CC-RRTMG_SW and exploring its maximum computing performance on GPU. First, a three-dimensional acceleration algorithm for CC-RRTMG_SW is proposed. Then, some optimization methods, such as decoupling data dependency, optimizing memory access, and I/O optimization, are studied. Finally, the optimized version of CC-RRTMG_SW is developed, namely CC-RRTMG_SW++. The experimental results demonstrate that the proposed acceleration algorithm and performance optimization methods are effective. CC-RRTMG_SW++ achieved good acceleration effects on different GPU architectures, such as NVIDIA Tesla K20, K40, and V100. Compared to RRTMG_SW running on a single Intel Xeon E5-2680 v2 CPU core, CC-RRTMG_SW++ obtained a speedup of 99.09\(\times\) on a single V100 GPU without I/O transfer. Compared to CC-RRTMG_SW, the computing efficiency of CC-RRTMG_SW++ increased by 174.46%.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 41931183, in part by the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (EarthLab), and in part by the GHFUND A under Grant ghfund202107013661.

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Authors and Affiliations

  1. School of Information Engineering, China University of Geosciences, Beijing, 100083, China

    Fei Li, Yuzhu Wang, Zhenzhen Wang & Xiaohui Ji

  2. Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100190, China

    Jinrong Jiang

  3. School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410004, China

    Xiaoyong Tang

  4. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    He Zhang

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  1. Fei Li
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  2. Yuzhu Wang
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Correspondence to Yuzhu Wang or He Zhang.

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The code generated and analyzed during this study is available in the Github repository: https://github.com/guirenbenxin/Heterogeneous-RRTMG_SW.

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Li, F., Wang, Y., Wang, Z. et al. CC-RRTMG_SW++: Further optimizing a shortwave radiative transfer scheme on GPU. J Supercomput 78, 17378–17402 (2022). https://doi.org/10.1007/s11227-022-04566-5

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