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Fault-tolerant parallel computing for DEM data blocks with layered dependent relationships based on redundancy mechanism

机译:基于冗余机制的分层依赖关系的DEM数据块的容错并行计算

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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.
机译:本文的目的是在数字地形分析(DTA)的并行化中建立一种定量的数据划分方法,以指导并行计算算法的设计。根据数字高程模型(DEM)的数据密集型特性,提出了一种数据依赖模型来描述数据块的层次关系。根据模型构建了DEM的并行调度策略和算法。随着数据或任务计算规模的增加,并行计算中还必须考虑计算的可靠性。提出了一种基于数据依赖图的容错并行计算方法。分别提出了两次冗余,三次冗余和部分冗余的并行计算算法,并讨论了它们各自的优点。最后,以DTA中的可见性算法为例,验证了该策略和方法的有效性。

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