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Test scheduling optimization for 3D network-on-chip based on cloud evolutionary algorithm of Pareto multi-objective
Author(s): Chuanpei Xu; Junhao Niu; Jing Ling; Suyan Wang
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Paper Abstract

In this paper, we present a parallel test strategy for bandwidth division multiplexing under the test access mechanism bandwidth constraint. The Pareto solution set is combined with a cloud evolutionary algorithm to optimize the test time and power consumption of a three-dimensional network-on-chip (3D NoC). In the proposed method, all individuals in the population are sorted in non-dominated order and allocated to the corresponding level. Individuals with extreme and similar characteristics are then removed. To increase the diversity of the population and prevent the algorithm from becoming stuck around local optima, a competition strategy is designed for the individuals. Finally, we adopt an elite reservation strategy and update the individuals according to the cloud model. Experimental results show that the proposed algorithm converges to the optimal Pareto solution set rapidly and accurately. This not only obtains the shortest test time, but also optimizes the power consumption of the 3D NoC.

Paper Details

Date Published: 5 March 2018
PDF: 16 pages
Proc. SPIE 10710, Young Scientists Forum 2017, 1071013 (5 March 2018); doi: 10.1117/12.2315901
Show Author Affiliations
Chuanpei Xu, Guilin Univ. of Electronic Technology (China)
Guangxi Key Lab. of Automatic Detection Technology and Instrument (China)
Junhao Niu, Guilin Univ. of Electronic Technology (China)
Guangxi Key Lab. of Automatic Detection Technology and Instrument (China)
Jing Ling, Guilin Univ. of Electronic Technology (China)
Guangxi Key Lab. of Automatic Detection Technology and Instrument (China)
Suyan Wang, Guilin Univ. of Electronic Technology (China)
Guangxi Key Lab. of Automatic Detection Technology and Instrument (China)


Published in SPIE Proceedings Vol. 10710:
Young Scientists Forum 2017
Songlin Zhuang; Junhao Chu; Jian-Wei Pan, Editor(s)

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