基于GSAA算法的组合电路最大功耗估计方法  

Maximum power estimation for CMOS combinational circuits based on genetic-simulated annealing algorithm

作　　者：陈志强[1] 吴晓波[1] 严晓浪[1] 

机构地区：[1]浙江大学超大规模集成电路设计研究所,浙江杭州310027

出　　处：《电路与系统学报》2005年第2期75-78,共4页Journal of Circuits and Systems

基　　金：国家自然科学基金资助项目(90207001)

摘　　要：最大功耗估计问题是一个NP难题。提出的方法利用遗传模拟退火算法(GSAA)在整个解空间快速搜索问题的最优解,实现组合电路最大功耗的快速、精确估计。仿真结果表明,提出的方法比基于遗传算法(GA)的估计方法在估算精度和收敛速度上都有提高,适合于大规模组合电路最大功耗的估计。Maximum power estimation is a NP-hard problem. An approach was presented to search for optimal solution quickly in whole solution space, and to obtain an accurate lower bound of the maximum power consumption using GSAA (genetic-simulated annealing algorithm). The experiments show that the approach generates the lower bound with the better quality than GA, improves the convergence acceleration, saves the computation time and is more suitable for estimating the power dissipation of large scale design.

关 键 词：CMOS组合电路 最大功耗估计 遗传模拟退火算法 遗传算法 

分 类 号：TN47[电子电信—微电子学与固体电子学]