Input/Output analysis and optimization for GRAPES regional model - Yang Bin; Wang Jingyu; Liu Weiguo; Cai Huiyi; Yu Fei; Deng Liantang; Huang Liping (Dianzi Jishu Yingyong)
The new generation Global/Regional Assimilation and PreEdiction System(GRAPES) is a homegrown numerical weather prediction software developed by China Meteorological Administration(CMA). As the requirements for model resolution and prediction timeliness increase, the Input/Output(I/O) performance of GRAPES becomes a critical performance bottleneck. This paper performs a deep analysis of I/O behavior for the GRAPES regional model，and proposes, designs and implements a high-performance I/O framework. This framework achieves a flexible and configurable output method through binary encoding and multiple I/O channels. At the same time, asynchronous I/O is included by non-blocking communication, which hides the I/O and communication overhead. The framework has been tested on the Sugon Pai supercomputer, and the results show that the framework can not only improve I/O performance by up to over ten times but also reduce the performance uncertainty caused by performance jitter.