An Integrated Optimization Approach for Nanohybrid Circuit Cell Mapping

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 constra...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on nanotechnology 2011-11, Vol.10 (6), p.1275-1284
Hauptverfasser: Yinshui Xia, Zhufei Chu, Hung, W. N. N., Lunyao Wang, Xiaoyu Song
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:1536-125X
1941-0085
DOI:10.1109/TNANO.2011.2131153