With the emergence of the multicore architecture and the increase of chip operating frequency, power optimization has become a key step of circuit logic synthesis. Aiming at the XNOR/OR circuits, with the goal of minimizing power, construct the optimal polarity fixed-polarity Reed–Muller (FPRM) circuits power optimization scheme. However, the power optimization for FPRM circuits is a multipeak combinatorial optimization problem, we first propose a metaheuristic optimization algorithm (MOA), which includes the global exploration optimizer, local deep exploitation optimizer, and initial population and uses the proposed differential evolution optimization, fierce wolf siege algorithm-based tabu search, and improved skew tent map to make the population evolve. Based on the proposed Huffman tree construction algorithm and MOA, we propose an efficient power optimization approach (EPOA) to find the minimum power FPRM circuit. Experimental results on the benchmark circuits confirm the effectiveness of EPOA.

中文翻译：

---

基于元启发式优化算法的固定极性 Reed-Muller 逻辑电路的高效功率优化方法

随着多核架构的出现和芯片工作频率的提高，功耗优化成为电路逻辑综合的关键步骤。针对XNOR/OR电路，以最小化功耗为目标，构建最优极性固定极性Reed-Muller (FPRM)电路功耗优化方案。然而，FPRM电路的功率优化是一个多峰组合优化问题，我们首先提出了一种元启发式优化算法（MOA），它包括全局探索优化器、局部深度开发优化器和初始种群，并使用所提出的差分进化优化，激烈基于wolf siege算法的禁忌搜索，以及改进的skew tent map使种群进化。基于提出的哈夫曼树构建算法和MOA，我们提出了一种高效的功率优化方法 (EPOA) 来找到最小功率 FPRM 电路。基准电路的实验结果证实了 EPOA 的有效性。