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

Autor: Ya-hui Chai (柴亚辉), Thanh-cuong Nguyen (阮青强), Weimin Xu, Wen-feng Shen
Rok vydání: 2011
Předmět:
Zdroj: Journal of Shanghai University (English Edition). 15:426-429
ISSN: 1863-236X
1007-6417
DOI: 10.1007/s11741-011-0763-3
Popis: 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.
Databáze: OpenAIRE
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