23 January 2017 A result-driven minimum blocking method for PageRank parallel computing
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Proceedings Volume 10322, Seventh International Conference on Electronics and Information Engineering; 103224E (2017) https://doi.org/10.1117/12.2265751
Event: Seventh International Conference on Electronics and Information Engineering, 2016, Nanjing, China
Abstract
Matrix blocking is a common method for improving computational efficiency of PageRank, but the blocking rules are hard to be determined, and the following calculation is complicated. In tackling these problems, we propose a minimum blocking method driven by result needs to accomplish a parallel implementation of PageRank algorithm. The minimum blocking just stores the element which is necessary for the result matrix. In return, the following calculation becomes simple and the consumption of the I/O transmission is cut down. We do experiments on several matrixes of different data size and different sparsity degree. The results show that the proposed method has better computational efficiency than traditional blocking methods.
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Wan Tao, Wan Tao, Tao Liu, Tao Liu, Wei Yu, Wei Yu, Gan Huang, Gan Huang, } "A result-driven minimum blocking method for PageRank parallel computing", Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103224E (23 January 2017); doi: 10.1117/12.2265751; https://doi.org/10.1117/12.2265751
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