DocumentCode :
1595303
Title :
A Hybrid Genetic Algorithm with Critical Primary Inputs Sharing and Minor Primary Inputs Bits Climbing for Circuit Maximum Power Estimation
Author :
Tian, Zhixin ; Liu, Yongpan ; Yang, Huazhong ; Wang, Hui
Author_Institution :
Tsinghua Univ., Beijing
Volume :
4
fYear :
2007
Firstpage :
183
Lastpage :
187
Abstract :
With continuously shrinking of ICs device feature sizes, input pattern dependent maximum power in a clock cycle (CMP) for digital circuit has become a challenging issue in power network verification and optimization. In this paper, a novel hybrid genetic algorithm (HGA) that takes advantages of critical primary inputs sharing and minor primary inputs bits climbing is proposed for CMP estimation. Critical and minor primary inputs are defined based on their possible contribution to CMP, which is defined as the fitness value for the input vector pair. Compared with simple genetic algorithm, our method achieves up to 25.7% improvement on CMP estimation for ISCAS85 benchmark circuits with a faster convergence speed and less than 6% computation overhead in average.
Keywords :
CMOS digital integrated circuits; estimation theory; genetic algorithms; clock cycle estimation; critical primary input sharing; digital CMOS integrated circuit; hybrid genetic algorithm; maximum power estimation; minor primary inputs bit climbing; optimization; power network verification; CMOS technology; Circuit noise; Clocks; Delay estimation; Digital circuits; Genetic algorithms; Power dissipation; Power supplies; Timing; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.49
Filename :
4344666
Link To Document :
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