Based on the research of population migration algorithms （PMAs）, a population migration genetic algo- rithm （PMGA） is proposed, combining a PMA with a genetic algorithm. A scheme of area and power optimization for...Based on the research of population migration algorithms （PMAs）, a population migration genetic algo- rithm （PMGA） is proposed, combining a PMA with a genetic algorithm. A scheme of area and power optimization for a ternary FPRM circuit is proposed by using the PMGA. Firstly, according to the ternary FPRM logic function expression, area and power estimation models are established. Secondly, the PMGA is used to search for the best area and power polarity. Finally, 10 MCNC Benchmark circuits are used to verify the effectiveness of the proposed method. The results show that the ternary FPRM circuits optimized by the PMGA saved 13.33% area and 20.00% power on average than the corresponding FPRM circuits optimized by a whole annealing genetic algorithm.展开更多
通过对杂草蝙蝠算法(Invasive Weed Bat Algorithm,IWBA)和三值FPRM(FixedPolarity Reed-Muller)电路函数表达式的研究,提出了一种三值FPRM电路延时和面积优化算法。算法首先建立延时估计模型,评估当前极性电路的适应度函数值;然后利用...通过对杂草蝙蝠算法(Invasive Weed Bat Algorithm,IWBA)和三值FPRM(FixedPolarity Reed-Muller)电路函数表达式的研究,提出了一种三值FPRM电路延时和面积优化算法。算法首先建立延时估计模型,评估当前极性电路的适应度函数值;然后利用三值极性转换算法,将二值基准测试电路转换为三值FPRM电路;最后利用IWBA算法进行三值FPRM电路延时和面积最佳极性搜索。实验对10个基准电路进行测试,结果表明:相比于蝙蝠算法(Bat Algorithm,BA),延时平均降低14.3%,面积平均节省66.0%。展开更多
基金supported by the Natural Science Foundation of Zhejiang Province(No.LY13F040003)the National Natural Science Foundation of China(Nos.61234002,61306041)the K.C.Wong Magna Fund in Ningbo University
文摘Based on the research of population migration algorithms （PMAs）, a population migration genetic algo- rithm （PMGA） is proposed, combining a PMA with a genetic algorithm. A scheme of area and power optimization for a ternary FPRM circuit is proposed by using the PMGA. Firstly, according to the ternary FPRM logic function expression, area and power estimation models are established. Secondly, the PMGA is used to search for the best area and power polarity. Finally, 10 MCNC Benchmark circuits are used to verify the effectiveness of the proposed method. The results show that the ternary FPRM circuits optimized by the PMGA saved 13.33% area and 20.00% power on average than the corresponding FPRM circuits optimized by a whole annealing genetic algorithm.
