@Article{cmc.2020.09860,
AUTHOR = {Lili He, Zhiwei Cai, Dantong Ouyang, Changshuai Wang, Yu Jiang, Chong Wang, Hongtao Bai},
TITLE = {A Revised Satellite Cloud-Derived Wind Inversion Algorithm Based on Computer Cluster},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {1},
PAGES = {373--388},
URL = {http://www.techscience.com/cmc/v64n1/39148},
ISSN = {1546-2226},
ABSTRACT = {In view of the satellite cloud-derived wind inversion has the characteristics of 
large scale, intensive computing and time-consuming serial inversion algorithm is very 
difficult to break through the bottleneck of efficiency. We proposed a parallel acceleration 
scheme of cloud-derived wind inversion algorithm based on MPI cluster parallel technique
in this paper. The divide-and-conquer idea, assigning winds vector inversion tasks to each 
computing unit, is identified according to a certain strategy. Each computing unit executes 
the assigned tasks in parallel, namely divide-and-rule the inversion task, so as to reduce the 
efficiency bottleneck of long inversion time caused by serial time accumulation. In the 
scheme of parallel acceleration based on MPI cluster, an algorithm based on performance 
prediction is proposed to effectively implement load balance of MPI clusters. Through the 
comparative analysis of experiment data using the parallel scheme of this parallel 
technology framework, it shows that this parallel technology has a certain acceleration 
effect on the cloud-derived wind inversion algorithm. The speedup of the MPI-based 
parallel algorithm reaches 14.96, which achieved the expected estimate. At the same time, 
this paper also proposes an efficiency optimization algorithm for cloud-derived wind 
inversion. In the case that the inversion of wind vector accuracy loss is minimal, the 
optimized algorithm execution time can be up to 13 times faster.},
DOI = {10.32604/cmc.2020.09860}
}