Abstract
With the development of satellite remote sensing technology, more and more requirements are put forward on the timeliness and stability of the satellite weather service system. The FY satellite rainfall estimate day knock off product algorithm runs longer, about 20 minutes, which affects the estimated rainfall product generated timeliness. Research and development of parallel optimization algorithms based on the needs of satellite meteorological services and their effectiveness in practical applications are necessary ways to enhance the high-performance and high-availability capabilities of satellite meteorological services. So aiming at this problem, we started the parallel algorithm research based on the analysis of precipitation estimation algorithm. Firstly, we explained the steps of precipitation estimated date knock off product algorithm; secondly, we analyzed the four main calculation module calculating the amount of algorithms; thirdly, multithreaded parallel algorithm and MPI parallelization was designed. Finally, the multithreaded parallel and MPI parallelization were realized. Experimental results show that the multithreaded parallel and MPI parallelization algorithm could greatly improve the overall degree of computational efficiency. And, MPI parallelization mode has a higher operating efficiency. The performance of parallel processing is closely related to the architecture of the computer. From the perspective of service scheduling and product algorithms, the MPI parallelization approach is adopted to achieve the purpose of improving service quality.
Highlights
We explained the steps of precipitation estimated date knock off product algorithm; secondly, we analyzed the four main calculation module calculating the amount of algorithms; thirdly, multithreaded parallel algorithm and MPI parallelization was designed
The parallelization algorithm based on multi-thread and the parallelization algorithm based on MPI are proposed for the parallelization of FY-3 satellite precipitation estimation
In order to verify the validity of the parallelization algorithm and compare it on the basis of this, we have realized the two parallelization methods respectively, and the experimental results and the correlation analysis are given
Summary
This paper aims to study the parallelization method of data reconciliation algorithm for meteorological satellite precipitation, so as to improve the generation efficiency of precipitation products and improve the service level of precipitation products. Lai Guoming et al [5] detailed analysis of fast multi-pole algorithm FMM (Fast Multipole Method) the basic principles. Su Shengqu and Liang Shizhen [7] pointed out that parallel computing as a modern computer is an important calculation method. This greatly optimizes the calculation process of the ant colony algorithm. A large-scale MPI parallel computing test was carried out to study the stability of the developed MPI parallelized region decomposition strategy and program optimization method [14]
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