Crosstalk Noise Analysis for Nano-Meter VLSI Circuits.

Abstract

Scaling of device dimensions into the nanometer process technology has led to a considerable reduction in the gate delays. However, interconnect delays have not scaled in proportion to gate delays, and global-interconnect delays account for a major portion of the total circuit delay. Also, due to process-technology scaling, the spacing between adjacent interconnect wires keeps shrinking, which leads to an increase in the amount of coupling capacitance between interconnect wires. Hence, coupling noise has become an important issue which must be modeled while performing timing verification for VLSI chips. As delay noise strongly depends on the skew between aggressor-victim input transitions, it is not possible to a priori identify the victim-input transition that results in the worst-case delay noise. This thesis presents an analytical result that would obviate the need to search for the worst-case victim-input transition and simplify the aggressor-victim alignment problem significantly. We also propose a heuristic approach to compute the worst-case aggressor alignment that maximizes the victim receiver-output arrival time with current-source driver models. We develop algorithms to compute the set of top-k aggressors in the circuit, which could be fixed to reduce the delay noise of the circuit. Process variations cause variability in the aggressor-victim alignment which leads to variability in the delay noise. This variability is modeled by deriving closed-form expressions of the mean, the standard deviation and the correlations of the delay-noise distribution. We also propose an approach to estimate the confidence bounds on the path delay-noise distribution. Finally, we show that the interconnect corners obtained without incorporating the effects of coupling noise could lead to significant errors, and propose an approach to compute the interconnect corners considering the impact of coupling noise.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64663/1/gravkis_1.pd