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Research and implementation of scalable parallel computing based on Map-Reduce
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作者 阮青强 沈文枫 +1 位作者 柴亚辉 徐炜民 《Journal of Shanghai University(English Edition)》 CAS 2011年第5期426-429,共4页
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 ... 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. 展开更多
关键词 map-reduce distributed computing n-body problem
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