基于整体退火遗传算法的低功耗极性转换

针对n变量逻辑函数在不同极性下所对应REED-MULLER(RM)电路功耗和面积不问的特点,对信号几率传递算法、多输入XOR/AND(异或/与)门的低功耗分解算法和多成份极性转换算法进行了深入研究,成功地将整体退火遗传算法(whole annealing genetic algorithm,WAGA)应用于RM电路最佳极件的搜索.通过对8个MCNC Benchmark测试表明,算法搜索到的最佳极性,其所对应RM电路的SYNOPSYS综合结果,与极性0时相比,功耗、面积和最大延时的平均节省分别达到了77.2%,62.4%和9.2%.

Low Power Polarity Conversion Based on the Whole Annealing Genetic Algorithm

For an n-variable logic function,the power dissipation and area of the REED-MULLER (RM) circuit corre-sponding to each polarity are different. Based on the propagation algorithm of signal probability, the decomposition algo-rithm of a multi-input XOR/AND gate, and the multiple segment algorithm of polarity conversion, this paper successfully applies the whole annealing genetic algorithm (WAGA) to find the best polarity of an RM circuit. Through testing eight large-scale circuits from the Microelectronics Center North Carolina (MCNC) Benchmark, the SYNOPSYS synthesis re-sults show that the RM circuits corresponding to the best polarity found using the proposed algorithm attain average power,area,and max delay savings of 77.2% ,62. 4% ,and 9.2% respectively,compared with those under polarity 0.