引用本文: 江岭, 汤国安, 宋效东, 刘凯, 阳建逸. 顾及粒度控制的格网DEM洼地和平坦区预处理并行算法[J]. 武汉大学学报 ( 信息科学版), 2014, 39(12): 1457-1462.
Jiang Ling, Tang Guoan, Song Xiaodong, Liu Kai, Yang Jianyi. Parallel DEM Preprocessing Algorithm with Granularity Control on Gridded Terrain Datasets[J]. Geomatics and Information Science of Wuhan University, 2014, 39(12): 1457-1462.
 Citation: Jiang Ling, Tang Guoan, Song Xiaodong, Liu Kai, Yang Jianyi. Parallel DEM Preprocessing Algorithm with Granularity Control on Gridded Terrain Datasets[J]. Geomatics and Information Science of Wuhan University, 2014, 39(12): 1457-1462.

## 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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