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中文摘要：
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,基于消息传递接口并行化工具,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下,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下完成计算任务,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。
英文摘要：
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-node Linux 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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