Proceedings of the 2007 international workshop on System level interconnect prediction
Proceedings of the 2007 international symposium on Physical design
Assessing carbon nanotube bundle interconnect for future FPGA architectures
Proceedings of the conference on Design, automation and test in Europe
Performance modeling and optimization for single- and multi-wall carbon nanotube interconnects
Proceedings of the 44th annual Design Automation Conference
CAD implications of new interconnect technologies
Proceedings of the 44th annual Design Automation Conference
On the modeling of resistance in graphene nanoribbon (GNR) for future interconnect applications
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Inductance modelling of SWCNT bundle interconnects using partial element equivalent circuit method
Journal of Computational Electronics
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Delay uncertainty in single- and multi-wall carbon nanotube interconnects
VDAT'12 Proceedings of the 16th international conference on Progress in VLSI Design and Test
Journal of Computational Electronics
Journal of Computational Electronics
Demystifying SWCNT-bundle-interconnects inductive behavior through novel modeling
Journal of Computational Electronics
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In this paper, we develop accurate and scalable models for the magnetic inductance in bundles of single-walled carbon nanotubes, which have been proposed as a means to alleviate the increasingly critical resistance problems associated with traditional copper interconnect in very large scale integration (VLSI) applications. The models consider the density and statistical distribution of both metallic and semiconducting nanotubes within the bundle. We evaluate the speed, accuracy, and scalability of our magnetic inductance modeling techniques and previously proposed inductance models. The inductance model with the best performance evaluates the magnetic inductance of nanotube bundles with excellent accuracy when compared to modeling each nanotube individually and provides orders of magnitude improvement in CPU time as the bundle size increases. Leveraging the magnetic inductance modeling techniques, we determine the relative impact of magnetic and kinetic inductance. Based on our results, the relative value of magnetic and kinetic inductance on single-walled carbon nanotube (SWCNT) bundles is highly dependent on the bundle geometry and the per unit length kinetic inductance