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Open AccessArticle

Using a GPU to Accelerate a Longwave Radiative Transfer Model with Efficient CUDA-Based Methods

1
School of Information Engineering, China University of Geosciences, Beijing 100083, China
2
School of Computer Science, The University of Sydney, Sydney, NSW 2006, Australia
3
Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(19), 4039; https://doi.org/10.3390/app9194039
Received: 8 August 2019 / Revised: 22 September 2019 / Accepted: 24 September 2019 / Published: 27 September 2019
(This article belongs to the Special Issue Energy-Efficient Internet of Things (IoT))
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. View Full-Text
Keywords: high-performance computing; graphics processing unit; compute unified device architecture; radiation transfer high-performance computing; graphics processing unit; compute unified device architecture; radiation transfer
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Wang, Y.; Zhao, Y.; Li, W.; Jiang, J.; Ji, X.; Zomaya, A.Y. Using a GPU to Accelerate a Longwave Radiative Transfer Model with Efficient CUDA-Based Methods. Appl. Sci. 2019, 9, 4039.

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