Fast high-order variation-aware IC interconnect analysis

Interconnects constitute a dominant source of circuit delay for modern chip designs. The variations of critical dimensions in modern VLSI technologies lead to variability in interconnect performance that must be fully accounted for in timing verification. However, handling a multitude of inter-die/intra-die variations and assessing their impacts on circuit performance can dramatically complicate the timing analysis. In this thesis, three practical interconnect delay and slew analysis methods are presented to facilitate efficient evaluation of wire performance variability. The first method is described in detail in Chapter III. It harnesses a collection of computationally efficient procedures and closed-form formulas. By doing so, process variations are directly mapped into the variability of the output delay and slew. This method can provide the closed-form formulas of the output delay and slew at any sink node of the interconnect nets fully parameterized, in-process variations. The second method is based on adjoint sensitivity analysis and driving point model. It constructs the driving point model of the driver which drives the interconnect net by using the adjoint sensitivity analysis method. Then the driving point model can be propagated through the interconnect network by using the first method to obtain the closedform formulas of the output delay and slew. The third method is the generalized second-order adjoint sensitivity analysis. We give the mathematical derivation of this method in Chapter V. The theoretical value of this method is it can not only handle this particular variational interconnect delay and slew analysis, but it also provides an avenue for automatical linear network analysis and optimization. The proposed methods not only provide statistical performance evaluations of the interconnect network under analysis but also produce delay and slew expressions parameterized in the underlying process variations in a quadratic parametric form. Experimental results show that superior accuracy can be achieved by our proposed methods.