中圖分類號: TP391 文獻(xiàn)標(biāo)識碼: A DOI:10.16157/j.issn.0258-7998.212422 中文引用格式: 楊斌,,王敬宇,,劉衛(wèi)國,等. GRAPES區(qū)域模式的輸入輸出分析和優(yōu)化[J].電子技術(shù)應(yīng)用,,2022,,48(1):39-45,52. 英文引用格式: Yang Bin,,Wang Jingyu,,Liu Weiguo,et al. Input/Output analysis and optimization for GRAPES regional model[J]. Application of Electronic Technique,,2022,,48(1):39-45,52.
Input/Output analysis and optimization for GRAPES regional model
Yang Bin1,,2,,Wang Jingyu3,Liu Weiguo1,,2,,Cai Huiyi2,Yu Fei4,,5,,Deng Liantang4,5,,Huang Liping4,,5
1.School of Software,Shandong University,,Jinan 250101,China,;2.National Supercomputing Center in Wuxi,,Wuxi 214072,,China; 3.National Research Center of Parallel Computer Engineering & Technology,,Beijing 100086,,China; 4.Numerical Weather Prediction Center of CMA,,Beijing 100081,,China;5.State Key Laboratory of Severe Weather,,Beijing 100081,,China
Abstract: 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.
Key words : I/O optimization,;asynchronous I/O,;GRAPES;CMA-MESO,;regional model
0 引言
天氣預(yù)報與人民財產(chǎn)和生命安全休戚相關(guān),。近年來高影響天氣事件(例如鄭州暴雨)的發(fā)生頻度和強(qiáng)度持續(xù)增加,嚴(yán)重影響經(jīng)濟(jì)社會發(fā)展,,威脅人民生命財產(chǎn)安全,。對高影響天氣的精準(zhǔn)預(yù)報已經(jīng)成為國際熱點(diǎn),以及國家防災(zāi)減災(zāi)決策中的關(guān)鍵和迫切需求,。自20世紀(jì)80年代起,,數(shù)值預(yù)報已成為國際天氣預(yù)報的主流發(fā)展趨勢,天氣形勢預(yù)報時效目前達(dá)到甚至超過7天,,而制作更精細(xì)的數(shù)值預(yù)報,,提高天氣預(yù)報準(zhǔn)確率的關(guān)鍵是進(jìn)一步提高數(shù)值預(yù)報的精確度[1]。超高分辨率模擬和高頻觀測資料的快速應(yīng)用是當(dāng)前提升數(shù)值預(yù)報精確度的關(guān)鍵,,也是極其重要又極具挑戰(zhàn)的計算應(yīng)用,。全球/區(qū)域多尺度統(tǒng)一的同化與數(shù)值預(yù)報系統(tǒng)(Global/Regional Assimilation and PreEdiction System,GRAPES)[2]應(yīng)運(yùn)而生,,GRAPES是我國歷時超過二十年自主研發(fā),,以多尺度通用非精力動力框架為核心開發(fā)建立的可插拔式的新一代通用數(shù)值分析同化與預(yù)報系統(tǒng)。目前GRAPES已成為我國中期數(shù)值天氣預(yù)報的業(yè)務(wù)化模式,,不僅能夠預(yù)報大尺度形勢場,,而且在要素預(yù)報(如降水量、風(fēng),、濕,、壓等)準(zhǔn)確性也在逐步提高,逐漸在預(yù)報業(yè)務(wù)一線發(fā)揮著越來越大的作用[3-5]。