Chinese Journal of Quantum Electronics, Volume. 25, Issue 4, 443(2008)
Hybrid quantum probabilistic coding genetic algorithm for hardware-software co-synthesis of embedded systems
Hardware-software HW-SW co-synthesis is a key step of future design of embedded systems which consists of two NP-complete problems. So it is a really hard and challenging task to optimiza-tion algorithms. A new hybrid evolutionary algorithm,called hybrid quantum probabilistic coding genetic algorithm(HQGA),is proposed to implement the co-synthesis of large scale multiprocessor embedded systems. In HQGA,a heuristic algorithm is combined with the quantum probabilistic coding genetic algorithm(QGA)to enhance the performance on the hard task. The experimental results show that HQGA has better performance than both HA and QGA on large scale HW/SW co-synthesis problems.
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GUO Rong-hua, LI Bin, ZHUANG Zhen-quan. Hybrid quantum probabilistic coding genetic algorithm for hardware-software co-synthesis of embedded systems[J]. Chinese Journal of Quantum Electronics, 2008, 25(4): 443
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Received: Sep. 29, 2007
Accepted: --
Published Online: Jun. 7, 2010
The Author Email: Rong-hua GUO (guoronghua@mail.ustc.edu.cn)
CSTR:32186.14.