A Novel GPU-Based Acceleration Algorithm for a Longwave Radiative Transfer Model

• Published in: Applied sciences 2020-01, Vol.10 (2), p.649
• Main Authors: Wang, Yuzhu, Zhao, Yuan, Jiang, Jinrong, Zhang, He
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Atmospheric circulation; Central processing units; Climate models; Climate system; compute unified device architecture; Cooling; CPUs; Efficiency; Fluxes; General circulation models; graphics processing unit; Graphics processing units; high performance computing; Long wave radiation; Meteorological satellites; Programming languages; Radiation; radiation transfer; Radiative transfer
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app10020649

Graphics processing unit (GPU)-based computing for climate system models is a longstanding research area of interest. The rapid radiative transfer model for general circulation models (RRTMG), a popular atmospheric radiative transfer model, can calculate atmospheric radiative fluxes and heating rates. However, the RRTMG has a high calculation time, so it is urgent to study its GPU-based efficient acceleration algorithm to enable large-scale and long-term climatic simulations. To improve the calculative efficiency of radiation transfer, this paper proposes a GPU-based acceleration algorithm for the RRTMG longwave radiation scheme (RRTMG_LW). The algorithm concept is accelerating the RRTMG_LW in the g- p o i n t dimension. After implementing the algorithm in CUDA Fortran, the G-RRTMG_LW was developed. The experimental results indicated that the algorithm was effective. In the case without I/O transfer, the G-RRTMG_LW on one K40 GPU obtained a speedup of 30.98× over the baseline performance on one single Intel Xeon E5-2680 CPU core. When compared to its counterpart running on 10 CPU cores of an Intel Xeon E5-2680 v2, the G-RRTMG_LW on one K20 GPU in the case without I/O transfer achieved a speedup of 2.35×.