@Article{cmc.2020.09701,
AUTHOR = {Tiejun Wang, Liu Zhuang, Julian M. Kunkel, Shu Xiao, Changming Zhao},
TITLE = {Parallelization and I/O Performance Optimization of a Global  Nonhydrostatic Dynamical Core Using MPI},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {63},
YEAR = {2020},
NUMBER = {3},
PAGES = {1399--1413},
URL = {http://www.techscience.com/cmc/v63n3/38883},
ISSN = {1546-2226},
ABSTRACT = {The Global-Regional Integrated forecast System (GRIST) is the nextgeneration 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.},
DOI = {10.32604/cmc.2020.09701}
}