DocumentCode :
1951903
Title :
A novel evolutionary algorithm for analog VLSI layout placement design
Author :
Zhang, Lihong ; Raut, Rabin ; Jiang, Yingtao
Author_Institution :
ECE Dept., Concordia Univ., Montreal, Que., Canada
fYear :
2004
fDate :
20-23 June 2004
Firstpage :
117
Lastpage :
120
Abstract :
In this paper, we present a novel macro-cell placement scheme following the optimization flow of a hybrid genetic algorithm (GA) controlled by the methodology of simulated annealing. It employs a two-dimensional bit-matrix representation and flexible operators. The dedicated cost function covers the special requirements of analog integrated circuits, including area, net length, aspect ratio, proximity, symmetry constraints, parasitic effect, etc. To study the algorithm parameters, the fractional factorial experiment using an orthogonal array has been employed, followed by a meta-GA to determine the exact parameter values. The proposed algorithm has been tested using several analog circuits, and appears superior to the simulated-annealing approaches mostly used for analog macro-cell placement.
Keywords :
VLSI; analogue integrated circuits; circuit optimisation; genetic algorithms; integrated circuit layout; integrated circuit modelling; integrated circuit testing; matrix algebra; simulated annealing; analog VLSI layout placement design; analog integrated circuits; cost function; evolutionary algorithm; hybrid genetic algorithm; macrocell placement scheme; meta genetic algorithm; optimization; orthogonal array; simulated annealing; two dimensional bit matrix representation; Algorithm design and analysis; Analog integrated circuits; Circuit simulation; Circuit testing; Cost function; Evolutionary computation; Genetic algorithms; Optimization methods; Simulated annealing; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2004. NEWCAS 2004. The 2nd Annual IEEE Northeast Workshop on
Print_ISBN :
0-7803-8322-2
Type :
conf
DOI :
10.1109/NEWCAS.2004.1359036
Filename :
1359036
Link To Document :
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