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High speed extraction of process model parameters for 70nm technology using a distributed genetic algorithm

M.Murakawa, Y.Oda, H.Amakawa, S.Baba, T.Higuchi, and K.Nishi
AIST, JP

Keywords: model calibration, genetic algorithm, parallel computation, B implantation, dual-Pearson profile

Abstract:
In this paper, we show, for the first time, GA application to process model calibration. We propose a distributed GA based calibration technique combined with the traditional local optimization algorithm, which reduces time for calibration considerably. Experimental results show calibration of 144 parameters can be completed with a few minutes, whereas it typically takes a human expert a few days. Our algorithm can be easily implemented on a coarse-grain parallel computer such as a PC cluster system or a multi processor workstation. GA, thus, can be a practical and robust tool for process/device calibration.

NSTI Nanotech 2003 Conference Technical Program Abstract

 
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