Parallelization and I/O Performance Optimization of a Global Nonhydrostatic Dynamical Core Using MPI  

作　　者：Tiejun Wang Liu Zhuang Julian MKunkel Shu Xiao Changming Zhao 

机构地区：[1]School of Computer Science,Chengdu University of Information Technology,Chengdu,610225,China [2]National Supercomputing Center in Wuxi,Wuxi,214072,China [3]Department of Computer Science,University of Reading,Berkshire,RG66UR,UK

出　　处：《Computers, Materials & Continua》2020年第6期1399-1413,共15页计算机、材料和连续体（英文）

基　　金：This work was supported by the National Key Research and Development Program of China under Grant No.2017YFC1502203.

摘　　要：The Global-Regional Integrated forecast System(GRIST)is the next-generation weather and climate integrated model dynamic framework developed by Chinese Academy of Meteorological Sciences.In this paper,we present several changes made to the global nonhydrostatic dynamical(GND)core,which is part of the ongoing prototype of GRIST.The changes leveraging MPI and PnetCDF techniques were targeted at the parallelization and performance optimization to the original serial GND core.Meanwhile,some sophisticated data structures and interfaces were designed to adjust flexibly the size of boundary and halo domains according to the variable accuracy in parallel context.In addition,the I/O performance of PnetCDF decreases as the number of MPI processes increases in our experimental environment.Especially when the number exceeds 6000,it caused system-wide outages(SWO).Thus,a grouping solution was proposed to overcome that issue.Several experiments were carried out on the supercomputing platform based on Intel x86 CPUs in the National Supercomputing Center in Wuxi.The results demonstrated that the parallel GND core based on grouping solution achieves good strong scalability and improves the performance significantly,as well as avoiding the SWOs.

关 键 词：MPI PARALLELIZATION performance optimization global nonhydrostatic dynamical core 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]