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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 × 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%. [ABSTRACT FROM AUTHOR]

High-performance computing for climate models has always been an interesting research area. It is valuable to nest a regional climate model within a global climate model, but large-scale simulation of the nesting or coupling severely challenges to the development of efficient parallel algorithms that fit well into multi-core clusters. This paper first presents research on the coupling of the Institute of Atmospheric Physics of Chinese Academy of Sciences Atmospheric General Circulation Model version 4.0 and the Weather Research and Forecasting model, then proposes an efficient parallel algorithm of the coupling. The algorithm includes initialization of input data, decomposition of computing grid and processes, parallel computing of component models, and data exchange by a coupler. By calling some subroutines of the Model Coupling Toolkit, the parallelization of the proposed algorithm is implemented. Experiments show that the parallel algorithm is very effective and scalable. The parallel efficiency of the algorithm on 1,024 CPU cores can reach up to 70%. Moreover, its parallel efficiency with respect to weak scalability is 72.56% on a multi-core cluster. [ABSTRACT FROM AUTHOR]

Load imbalance is a common problem to be tackled urgently in large scale data-driven simulation systems or data intensive computing. According to the coupler, the Chinese Academy of Sciences-Earth System Model (CAS-ESM) implements one-way nesting of the Institute of Atmospheric Physics of Chinese Academy of Sciences Atmospheric General Circulation Model version 4.0 (IAP AGCM4.0) and Weather Research and Forecasting model (WRF). The METGRID (meteorological grid) and REAL program modules in the WRF are used to process meteorological data. In the CAS-ESM, the load of the METGRID module is seriously unbalanced on many CPU cores. The load imbalance has a serious impact on the processing speed of meteorological data, so this study designs an optimization algorithm to solve the problem. Numerical experiments show that compared to before optimization, the optimization algorithm can solve the load imbalance of the METGRID, and the computation speed of the METGRID and REAL modules after optimization on 64 CPU cores is about 7.2 times faster than before. Meanwhile, the whole computation speed of the CAS-ESM can improve by 217.53%. In addition, results indicate that they also can reach to a similar speedup on different numbers of CPU cores. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The earth system model is one of the most complicated computer simulation software in the human development history, which is the basis of understanding and predicting the climate change, and an important tool to support the climate change related decisions. CAS-ESM, Chinese Academy of Science Earth System Model, is developed by the Institute of Atmospheric Physics(IAP) and its cooperators. This system contains the complete components of the climate system and ecological environment system including global atmospheric general circulation model(AGCM), global oceanic general circulation model(OGCM), ice model, land model, atmospheric chemistry model, dynamic global vegetation model(DGVM), ocean biogeochemistry model(OBM) and regional climate model(RCM), etc. Since CAS-ESM is a complex system and is designed as a scalable and pluggable system, a parallel software platform(SC-ESSP) is needed. SC-ESSP will be developed as an open software platform running on Chinese earth system numerical simulation facilities for different developers and users, which requires that the component models need to be standard and unified, and the platform should be pluggable, high performance and easy-to-use. To achieve this goal, based on the platform of Community Earth System Model(CESM), a parallel software application platform named SC-ESAP is designed for CAS-ESM, mainly including compile and run scripts, standard and unified component models, 3-D coupler component, coupler interface creator and some parallel and optimization work. A component framework SC-ESMF will be developed based on the framework SC-Tangram for the more distant future. [ABSTRACT FROM AUTHOR]