Delay estimates for graphene nanoribbons: A novel measure of fidelity and experiments with global routing trees

With extreme miniaturization of traditional CMOS devices in deep sub-micron design levels, the delay of a circuit, as well as power dissipation and area are dominated by interconnections between logic blocks. In an attempt to search for alternative materials, Graphene nanoribbons (GNRs) have been found to be potential for both transistors and interconnects due to its outstanding electrical and thermal properties. GNRs provide better options as materials used for global routing trees in VLSI circuits. However, certain special characteristics of GNRs prohibit direct application of existing VLSI routing tree construction methods for the GNR-based interconnection trees. In this paper, we address this issue possibly for the first time, and propose a heuristic method for construction of GNR-based minimum-delay Steiner trees based on linear-cum-bending hybrid delay model. Experimental results demonstrate the effectiveness of our proposed methods. We propose a novel technique for analyzing the relative accuracy of the delay estimates using rank correlation and statistical significance test. We also compute the delays for the trees generated by hybrid delay heuristic using Elmore delay approximation and use them for determining the relative accuracy of the hybrid delay estimate.