Modified Genetic Algorithm Based Method on Low-Power Mapping in Network-on-chip
- 10.2991/asei-15.2015.366How to use a DOI?
- Network-on-Chip; low-power; mapping; modified genetic algorithm; structural feature; better initial solution
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.
- © 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/).
Cite this article
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 -