Optimization of best polarity searching for mixed polarity reed-muller logic circuit

2015 28th IEEE International System-on-Chip Conference (SOCC) Pub Date : 2015-09-01 DOI:10.1109/SOCC.2015.7406962

Limin Xiao, Zhenxue He, Li Ruan, Rong Zhang, Tongsheng Xia, Xiang Wang

引用次数: 4

Abstract

At present, although genetic algorithm (GA) is widely used in best polarity searching of MPRM logic circuit, there are few literatures pay attention to the polarity conversion sequence of the polarity set waiting for evaluation. An improved best polarity searching approach (IBPSA) based on GA is presented to optimize the polarity conversion sequence of polarity set and speed up the best polarity searching of MPRM logic circuits. In addition, we present an improved nearest neighbor (INN) to obtain the best polarity conversion sequence of the polarity set waiting for evaluation in each generation of GA and apply elitism strategy to IBPSA to guarantee its global convergence. Our proposed IBPSA is implemented in C and a comparative analysis has been presented for MCNC benchmark circuits. The experimental results show that the IBPSA can greatly reduce the time of best polarity searching of MPRM logic circuits compared to the approaches neglecting polarity conversion sequence.

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混合极性reed-muller逻辑电路的最佳极性搜索优化

目前，虽然遗传算法被广泛应用于MPRM逻辑电路的最佳极性搜索，但很少有文献关注待评估极性集的极性转换顺序。提出了一种改进的基于遗传算法的最佳极性搜索方法(IBPSA)，以优化极性集的极性转换顺序，加快MPRM逻辑电路的最佳极性搜索速度。此外，我们提出了一种改进的最近邻算法(INN)来获得每一代遗传算法中等待评估的极性集的最佳极性转换序列，并将精英化策略应用于IBPSA以保证其全局收敛。我们提出的IBPSA在C语言中实现，并对MCNC基准电路进行了比较分析。实验结果表明，与忽略极性转换顺序的方法相比，IBPSA可以大大缩短MPRM逻辑电路的最佳极性搜索时间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2015 28th IEEE International System-on-Chip Conference (SOCC)

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