基于GPU-OpenACC的气候模式加速优化研究  

Research on Accelerated Optimization of Climate Models Based on GPU-OpenACC

作　　者：肖洒[1] 魏敏[1] 邓帅 徐达 张晨琛[2] XIAO Sa;WEI Min;DENG Shuai;XU Da;ZHANG Chenchen(National Meteorological Information Centre,Beijing 100081;Jilin Climate Center,Changchun 130062)

机构地区：[1]国家气象信息中心,北京100081 [2]吉林省气候中心,长春130062

出　　处：《气象》2019年第7期1001-1008,共8页Meteorological Monthly

基　　金：公益性行业(气象)科研专项(GYHY201306062);国家重点研发计划(2016YFA0602102)共同资助

摘　　要：为使数值模式适应异构架构在高性能计算领域的快速发展趋势,本文基于OpenACC语言,对气候模式BCC_AGCM3.0中动力框架三段程序段进行GPU加速优化试验。通过异步执行设置、循环内移、数据管理及向量参数化配置等方式,对模式中计算密集部分程序段进行GPU加速并行化,并进行了优化运行效率对比及正确性验证。试验结果表明,BCC_AGCM3.0模式中三段程序段GPU加速后效率提升均在3倍以上,BCC_AGCM气候模式全球涡度均方根相对误差控制在一定范围之内。加速方法及策略对于数值天气气候模式在异构环境下的移植与优化具有一定参考价值。In order to make the numerical model adapt to the fast development trend of high performance computing with hybrid architecture, based on the OpenACC, this paper presents the GPU accelerated optimization test for the three-segment procedure which is Beijing Climate Center Atmospheric General Circulation Model version 3.0 (BCC_AGCM3.0) in dynamic part. By means of asynchronous execution settings, cyclic inward migration, data management and vector parameterized configuration, we parallel the GPU acceleration of the computationally intensive part of the program segments in model, compare the optimization efficiency and validate the correctness. The experimental results show that the efficiency of the three-stage GPU acceleration in BCC_AGCM climate model, is increased by more than three times and the relative error of global vorticity root mean square (RMS) is controlled within a certain range. The acceleration methods and strategies are valuable for transplanting and optimizing numerical weather and climate models in heterogeneous environments.

关 键 词：BCC_AGCM GPU OpenACC 异构 

分 类 号：P409[天文地球—大气科学及气象学]