Research and implementation of scalable parallel computing based on Map-Reduce

被引:0
|
作者
阮青强 [1 ]
沈文枫 [1 ]
柴亚辉 [1 ,2 ]
徐炜民 [1 ]
机构
[1] School of Computer Engineering and Science,Shanghai University
[2] School of Information Engineering,East China Jiaotong University
关键词
Map-Reduce; distributed computing; N-body problem;
D O I
暂无
中图分类号
TP338.6 [并行计算机];
学科分类号
081201 ;
摘要
As a parallel programming model,Map-Reduce is used for distributed computing of massive data.Map-Reduce model encapsulates the details of parallel implementation,fault-tolerant processing,local computing and load balancing,etc.,provides a simple but powerful interface.In case of having no clear idea about distributed and parallel programming,this interface can be utilized to save development time.This paper introduces the method of using Hadoop,the open-source Map-Reduce software platform,to combine PCs to carry out scalable parallel computing.Our experiment using 12 PCs to compute N-body problem based on Map-Reduce model shows that we can get a 9.8x speedup ratio.This work indicates that the Map-Reduce can be applied in scalable parallel computing.
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页码:426 / 429
页数:4
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