An Integrated Optimization Approach for Nanohybrid Circuit Cell Mapping

Authors:
Yinshui Xia;Zhufei Chu;William N. N. Hung;Lunyao Wang;Xiaoyu Song
Affiliations:
School of Information Science and Engineering, Ningbo University, Ningbo, China;School of Information Science and Engineering, Ningbo University, Ningbo, China;Synopsys, Inc. , Mountain View, USA;School of Information Science and Engineering, Ningbo University, Ningbo, China;Department of Electrical and Computer Engineering, Portland State University, Portland, USA
Venue:
IEEE Transactions on Nanotechnology
Year:
2011

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Abstract

This paper presents an integrated optimization approach for nanohybrid circuit (CMOS/nanowire/molecular hybrid) cell mapping. The method integrates Lagrangian relaxation and memetic search synergistically. Based on encoding manipulation with appropriate population and structural connectivity constraints, 2-D block crossover, mutation, and self-learning operators are developed in a concerted way to obtain an effective mapping solution. In addition, operative buffer insertion is performed to leverage the quality of routing. Numerical results from ISCAS benchmarks and comparison with previous methods demonstrate the effectiveness of the modeling and solution methodology. The method outperforms the previous work in terms of CPU runtime, timing delay, and circuit scale.