BibTeX

@article{PAIPOOAGND20,
	author	 = {Tiejun Wang and Zhuang Liu and Julian Kunkel and Changming Zhao},
	title	 = {{Parallelization and I/O Performance Optimization of a Global Nonhydrostatic Dynamical Core using MPI}},
	year	 = {2020},
	month	 = {04},
	editor	 = {},
	publisher	 = {Tech Science Press},
	journal	 = {Computers, Materials and Continua},
	series	 = {Volume 63, Issue 3},
	pages	 = {1399-1413},
	issn	 = {1546-2226},
	doi	 = {https://doi.org/10.32604/cmc.2020.09701},
	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.},
}