Estimation of maximum power and instantaneous current using a genetic algorithm

Yi-Min Jiang, Kwang-Ting Cheng, Angela Krstic
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引用次数: 75

Abstract

We present a genetic-algorithm-based approach for estimating the maximum power dissipation and instantaneous current through supply lines for CMOS circuits. Our approach can handle large combinational and sequential circuits with arbitrary but known delays. To obtain accurate results we extract the timing and current information from transistor-level and general-delay gate-level simulation. Our experimental results show that the patterns generated by our approach produce on the average a lower bound on the maximum power which is 41% tighter than the one obtained by weighted random patterns for estimating the maximum power. Also, our lower bound for the maximum instantaneous current is 21% tighter as compared to the weighted random patterns.
用遗传算法估计最大功率和瞬时电流
我们提出了一种基于遗传算法的方法来估计CMOS电路的最大功耗和瞬时电流。我们的方法可以处理具有任意但已知延迟的大型组合和顺序电路。为了获得准确的结果,我们从晶体管级和通用延迟门级仿真中提取时序和电流信息。我们的实验结果表明,我们的方法产生的模式产生的最大功率的平均下界比加权随机模式获得的估计最大功率的下界严格41%。此外,与加权随机模式相比,我们的最大瞬时电流下界要紧21%。
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