The objective of this paper is to build a quantitative method of data partition in parallelisation of digital terrain analysis DTA so as to guide the design of algorithms in parallel computing. According to the data-intensive characteristics of the digital elevation model DEM, a data dependency model is proposed to describe the hierarchical relationships of data blocks. The parallel schedule policies and algorithms for the DEM are built according to the model. With the increase of computing scale in data or tasks, the reliability of the calculation must also be considered in parallel computing. A fault-tolerant parallel computing method is proposed based on the data dependence graph. Respectively, this paper puts forward parallel computing algorithms of two times redundant, three times redundant and partially redundant, with a discussion of their respective advantages. Finally, a visibility algorithm in DTA as an example is used to verify the validity of the strategies and methods.
['Wanfeng Dou', 'Shoushuai Miao', 'Yan Li']
Fault-tolerant parallel computing for DEM data blocks with layered dependent relationships based on redundancy mechanism