首页> 外文会议> >A framework for estimating maximum power dissipation in CMOS combinational circuits using genetic algorithms
【24h】

A framework for estimating maximum power dissipation in CMOS combinational circuits using genetic algorithms

机译:使用遗传算法估算CMOS组合电路中最大功耗的框架

获取原文

摘要

Assessing the maximum power dissipated by a CMOS combinational circuit is a complex problem because the power dissipated is input-pattern dependent. Simulation techniques are impractical, especially for large circuits, since the number of simulation runs needed increases exponentially with the number of inputs to the circuit. In this paper a genetic algorithm (GA) based approach is presented for generating a sequence of input vectors that tend to continuously maximize the switching activity of the circuit and hence the maximum power dissipated. The GA used evolves candidate input vectors while making use of a logic simulator to compute the fitness of each candidate. Experimentation with different GA parameters was carried out in order to derive an optimal set of working parameters for the GA. The performance of the GA technique was evaluated using "test circuits" whose topology allows simple analysis to determine the maximum number of simultaneous transitions possible for the circuits. In addition to this, some circuits from the ISAC-85 benchmark suite of circuits were also tested. The GA method was found to significantly out perform simulation-based techniques, especially in terms of CPU time expenditures.
机译:评估CMOS组合电路的最大功耗是一个复杂的问题,因为功耗是与输入模式有关的。仿真技术是不切实际的,特别是对于大型电路而言,因为所需的仿真运行次数会随电路输入的数量呈指数增长。在本文中,提出了一种基于遗传算法(GA)的方法,用于生成一系列输入矢量,这些输入矢量趋向于不断最大化电路的开关活动,从而最大程度地消耗功率。所使用的GA在使用逻辑模拟器计算每个候选者的适应度的同时,发展了候选者输入向量。为了获得最佳的GA工作参数,进行了不同GA参数的实验。 GA技术的性能是使用“测试电路”评估的,该拓扑的拓扑结构允许通过简单的分析来确定电路可能同时发生的最大跃迁数。除此之外,还对ISAC-85基准测试套件中的一些电路进行了测试。发现GA方法明显优于基于仿真的技术,特别是在CPU时间方面。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号