Modified Genetic Algorithm Based Method on Low-Power Mapping in Network-on-chip

DOI

10.2991/asei-15.2015.366How to use a DOI?

Keywords

Network-on-Chip; low-power; mapping; modified genetic algorithm; structural feature; better initial solution

Abstract

Focusing on the power decreasing of large-scale applications in network-on-chip, this paper proposed a modified genetic algorithm based method on low-power mapping. With communication weights of task nodes and structural features of mapping platform, this method acquired better initial mapping solution set with the consideration of task node priority and its connection. Moreover, we introduced the roulette wheel selection, best-neighbor selection and reverse evolution, and selected the initial solution with a certain probability at each iteration to prevent the algorithm stagnation. Experimental results show that, when maintaining the same task model and mapping platform, compared with the genetic algorithm and random mapping algorithm, our proposed algorithm greatly decreases the energy consumption.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qi-hua Dai
AU  - Qin-rang Liu
AU  - Jian-liang Shen
AU  - Miao Sun
PY  - 2015/05
DA  - 2015/05
TI  - Modified Genetic Algorithm Based Method on Low-Power Mapping in Network-on-chip
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 1837
EP  - 1846
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.366
DO  - 10.2991/asei-15.2015.366
ID  - Dai2015/05
ER  -