Share Email Print
cover

Proceedings Paper

A result-driven minimum blocking method for PageRank parallel computing
Author(s): Wan Tao; Tao Liu; Wei Yu; Gan Huang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper 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.

Paper Details

Date Published: 23 January 2017
PDF: 7 pages
Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103224E (23 January 2017); doi: 10.1117/12.2265751
Show Author Affiliations
Wan Tao, Anhui Polytechnic Univ. (China)
Key Lab. of Computer Application Technology (China)
Tao Liu, Anhui Polytechnic Univ. (China)
Key Lab. of Computer Application Technology (China)
Wei Yu, Anhui Polytechnic Univ. (China)
Gan Huang, Anhui Polytechnic Univ. (China)


Published in SPIE Proceedings Vol. 10322:
Seventh International Conference on Electronics and Information Engineering
Xiyuan Chen, Editor(s)

© SPIE. Terms of Use
Back to Top