2010 IEEE Second International Conference on Cloud Computing Technology and Science (2010)
Indianapolis, Indiana USA
Nov. 30, 2010 to Dec. 3, 2010
Many scientific applications suffer from the lack of a unified approach to support the management and efficient processing of large-scale data. The Twister MapReduce Framework, which not only supports the traditional MapReduce programming model but also extends it by allowing iterations, addresses these problems. This paper describes how Twister is applied to several kinds of scientific applications such as BLAST, MDS Interpolation and GTM Interpolation in a non-iterative style and to MDS without interpolation in an iterative style. The results show the applicability of Twister to data parallel and EM algorithms with small overhead and increased efficiency.
Twister, Iterative MapReduce, Cloud, Scientific Applications
T. Wu, J. Qiu, B. Zhang, Y. Ruan, A. Hughes and G. Fox, "Applying Twister to Scientific Applications," 2010 IEEE Second International Conference on Cloud Computing Technology and Science(CLOUDCOM), Indianapolis, Indiana USA, 2010, pp. 25-32.