Abstract
Climatic simulations rely heavily on high-performance computing. As one of the atmospheric radiative transfer models, the rapid radiative transfer model for general circulation models (RRTMG) is used to calculate the radiative transfer of electromagnetic radiation through a planetary atmosphere. Radiation physics is one of the most time-consuming physical processes, so the RRTMG presents large-scale and long-term simulation challenges to the development of efficient parallel algorithms that fit well into multicore clusters. This paper presents a method for improving the calculative efficiency of radiation physics, an RRTMG long-wave radiation scheme (RRTMG_LW) that is accelerated on a graphics processing unit (GPU). First, a GPU-based acceleration algorithm with one-dimensional domain decomposition is proposed. Then, a second acceleration algorithm with two-dimensional domain decomposition is presented. After the two algorithms were implemented in Compute Unified Device Architecture (CUDA) Fortran, a GPU version of the RRTMG_LW, namely G-RRTMG_LW, was developed. Results demonstrated that the proposed acceleration algorithms were effective and that the G-RRTMG_LW achieved a significant speedup. In the case without I/O transfer, the 2-D G-RRTMG_LW on one K40 GPU obtained a speed increase of 18.52× over the baseline performance on a single Intel Xeon E5-2680 CPU core.
Highlights
With the rapid development of computer technology, high-performance computing (HPC) is employed in a wide range of real-world applications [1,2,3]
In the CAS–Earth system models (ESMs), the Institute of Atmospheric Physics (IAP) AGCM4.0 is with a 1.4◦ × 1.4◦ horizontal resolution and 51 levels in the vertical direction, so here, the RRTMG_LW has 128 × 256 = 32,768 horizontal grid points
Transfer, the 1-D G-RRTMG_LW achieved a speedup of 10.57× compared to its counterpart running on one central processing unit (CPU) core of an Intel Xeon E5-2680 v2 whereas, using one K40 graphics processing unit (GPU) in the case without I/O
Summary
With the rapid development of computer technology, high-performance computing (HPC) is employed in a wide range of real-world applications [1,2,3]. As the foundational model for all radiation development, the LBLRTM is an accurate, efficient, and highly flexible model for calculating spectral transmittance and radiance, but it still demands enormous computing resources for long-term climatic simulation [16] To address this issue, several rapid radiative models with fast calculations of radiative flux and heating rates have already appeared, such as the rapid radiative transfer model (RRTM) [17]. Many studies show that radiative transfer is relatively time-consuming, taking up to 30–50 percent of the total computing time in numerical weather and climate simulations [27,28] To address this issue, it is beneficial to use GPU technology to accelerate the RRTMG in order to greatly improve its computational performance. The last section concludes the paper with a summary and proposal for future work
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