计算机工程与应用 ›› 2013, Vol. 49 ›› Issue (16): 40-42.

• 理论研究、研发设计 • 上一篇    下一篇

基于MapReduce的并行石漠化CA模型

张学锋1,余  利1,胡宝清2,严国全1,李  博1   

  1. 1.安徽工业大学 计算机学院,安徽 马鞍山 243032
    2.广西师范学院 资源与环境科学学院,南宁 530001
  • 出版日期:2013-08-15 发布日期:2013-08-15

Parallel rocky desertification CA model based on MapReduce

ZHANG Xuefeng1, YU Li1, HU Baoqing2, YAN Guoquan1, LI Bo1   

  1. 1.Computer Department,Anhui University of Technology, Ma’anshan, Anhui 243032, China
    2.Department of Resources and Environmental Science, Guangxi Teachers Education University, Nanning 530001, China
  • Online:2013-08-15 Published:2013-08-15

摘要: 针对石漠化演化模拟预测CA模型在单机上训练和运行时间较长的问题。给出了MapReduce编程模型实现的并行化石漠化CA模型,并在用普通PC搭建的Hadoop集群上进行研究实验。实验结果表明,在Hadoop集群上实现的MapReduce并行化石漠化CA模型具有较好的加速比。

关键词: 云计算, 并行计算, MapReduce模型, CA模型, 石漠化

Abstract: According to the problem that the CA model of rocky desertification evolution simulation and prediction runs in a single PC has a long time. This paper gives a parallel rocky desertification CA model based on MapReduce programming model, and performs research test in a Hadoop cluster built by the ordinary PC, the experimental results show that the parallel MapReduce rocky desertification CA model implemented in the Hadoop group has better speedup.

Key words: cloud computing, parallel computing, MapReduce model, CA model, rocky desertification