h-gamma: an RC delay metric based on a gamma distribution approximation of the homogeneous response
Proceedings of the 1998 IEEE/ACM international conference on Computer-aided design
A delay metric for RC circuits based on the Weibull distribution
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Delay and slew metrics using the lognormal distribution
Proceedings of the 40th annual Design Automation Conference
Simple metrics for slew rate of RC circuits based on two circuit moments
Proceedings of the 40th annual Design Automation Conference
Performance analysis of carbon nanotube interconnects for VLSI applications
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
ACM Journal on Emerging Technologies in Computing Systems (JETC)
ISQED '07 Proceedings of the 8th International Symposium on Quality Electronic Design
Single-walled carbon nanotube electronics
IEEE Transactions on Nanotechnology
Luttinger liquid theory as a model of the gigahertz electrical properties of carbon nanotubes
IEEE Transactions on Nanotechnology
Modeling Crosstalk Effects in CNT Bus Architectures
IEEE Transactions on Nanotechnology
A simple metric for slew rate of RC circuits based on two circuit moments
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Statistical interconnect metrics for physical-design optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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In this paper, a comprehensive and fast method is presented for the timing analysis of process variations on single-walled carbon nanotube (SWCNT) bundles. Unlike previous works that based on SPICE tools to estimate the delay, this paper proposes a closed-form solution for SWCNT interconnect timing analysis. With the assumption that the process variations are independent random variables, the delay of SWCNT bundles are mapped to a linear function of the variation variables, and efficiently calculated in the form of probability density functions (PDFs). Compared to SPICE-based solutions, this approach not only saves considerable computation time, but also provides a more comprehensive result, for it shows a compound impact of all variations, and covers all of the potential cases with their corresponding probabilities, rather than only one parameter can vary at a time, and only a worst case estimation is considered. The experiment results show that this solution bears little loss while providing the above mentioned advantages. Compared with SPICE-based Monte Carlo simulations, the experiments report the error in mean and standard deviation of delay to be 1.5% and 1.7% respectively.