顾及粒度控制的格网DEM洼地和平坦区预处理并行算法

Parallel DEM Preprocessing Algorithm with Granularity Control on Gridded Terrain Datasets

  • 摘要: 针对现有格网DEM洼地和平坦区处理并行算法进行数据处理时未考虑并行粒度等问题,在分析了洼地和平坦区处理串行算法的基础上,基于消息传递接II并行化工具,构建了顾及粒度控制的格网DEM洼地和平坦区处理并行算法。在配置Linux操作系统的集群环境卜,利用不同大小的DEM数据,测试了算法的并行性能,结果表明:顾及粒度控制的并行M&V算法可以在任意并行粒度卜完成计算任务,具有较好的并行性能。而且,对于某一给定的DEM数据,存在一个合适的并行粒度使得M&V算法的并行性能最佳。

     

    Abstract: Exiting parallel DEM preprocessing algorithms that do not consider parallel granularity.This paper presents a parallel DEM preprocessing algorithm with granularity control based on the analysis of the sequential algorithm proposed by Moran and Vezina(M&V algorithm).A Message Passing Interface(MPI) library is applied to implement the parallel algorithm. The parallel performance of the proposed algorithm is assessed by two gridded DEMs with different sizes on a multi-nodeLinux cluster. The application results show that the parallel M&V algorithm can complete the computing tasks when filling sinks and removing flat areas at any granuality,and it outputs an optimal granularity to achieve the best parallel performance for a given DEM dataset.

     

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