In advanced ASIC/SoC physical designs, interconnect parasitic extraction is one of the important factors to determine the accuracy of timing analysis. We present a formula-based method to efficiently extract interconnect capacitances of interconnects with dummy fills for VLSI designs. The whole flow is as follows: 1) in each process, obtain capacitances per unit length using a 3-D field solver and then create formulas, and 2) in the actual design phase, execute a well-known 2.5-D capacitance extraction. Our results indicated that accuracies of the proposed formulas were almost within 3% error. The proposed formula-based method can extract interconnect capacitances with high accuracy for VLSI circuits. Moreover, we present formulas to evaluate the effect of dummy fills on interconnect capacitances. These can be useful for determining design guidelines, such as metal density before the actual design, and for analyzing the effect of each structural parameter during the design phase.

Floating dummy metal fills inserted for planarization of multi-dielectric layers have created serious problems because of increased interconnect capacitance and the enormous number of fills. We present new dummy filling methods to reduce the interconnect capacitance and the number of dummy metal fills needed. These techniques include three ways of filling: 1) improved floating square fills, 2) floating parallel lines, and 3) floating perpendicular lines (with spacing between dummy metal fills above and below signal lines). We also present efficient formulas for estimating the appropriate spacing and number of fills. In our experiments, the capacitance increase using the conventional regular square method was 13.1%, while that using the methods of improved square fills, extended parallel lines, and perpendicular lines were 2.7%, 2.4%, and 1.0%, respectively. Moreover, the number of necessary dummy metal fills can be reduced by two orders of magnitude through use of the parallel line method.

We present a practical method of dealing with the influences of floating dummy metal fills, which are inserted to assist planarization by chemical-mechanical polishing (CMP) process, in extracting interconnect capacitances for system-on-chip (SoC) designs. The method is based on reducing the thicknesses of dummy metal layers according to electrical field theory. We also clarify the influences of dummy metal fills on the parasitic capacitance, signal delay, and crosstalk noise. Moreover, we address that interlayer dummy metal fills have more significant influences than intralayer ones in terms of the impact on coupling capacitances. When dummy metal fills are ignored, the error of capacitance extraction can be more than 30%, whereas the error of the proposed method is less than about 10% for many practical geometries. We also demonstrate, by comparison with capacitance results measured for a 90-nm test chip, that the error of the proposed method is less than 8%.

Simple closed-form expressions for efficiently calculating on-chip interconnect capacitances are presented. The formulas are expressed with second-order polynomial functions which do not include exponential functions. The runtime of the proposed formulas is about 2-10 times faster than those of existing formulas. The root mean square (RMS) errors of the proposed formulas are within 1.5%, 1.3%, 3.1%, and 4.6% of the results obtained by a field solver for structures with one line above a ground plane, one line between ground planes, three lines above a ground plane, and three lines between ground planes, respectively. The proposed formulas are also superior in accuracy to existing formulas.

In general, a corner model with best- and worst-case delay conditions is used in static timing analysis (STA). The best- and worst-case delays of a stage are defined as the fastest and slowest delays from a cell input to the next cell input. In this paper, we present a methodology for determining the parameters that yield the best- and worst-case delays when interconnect structural parameters have the minimum and maximum values with process variations. We also present analysis results of our circuit model using the methodology. The min and max conditions for the time constant are found to be (+Δw, +Δt, +Δh) & (-Δw, -Δt, -Δh), respectively. Here, +Δ or -Δ means the max or min corner value of each parameter variation, where w is the width, t is the interconnect thickness, and h is the height. Best and worst conditions for delay time are as follows: 1) given a circuit with an optimum driver, dense interconnects, and small branch capacitance, the best and worst conditions are respectively (-Δw, +Δt, +Δh) & (+Δw, +Δt, -Δh), 2) given driver and/or via resistances that are higher than the interconnect resistance, dense interconnects, and small branch capacitance, they are (-Δw, -Δt, +Δh) & (+Δw, +Δt, -Δh), and 3) for other conditions, they are (+Δw, +Δt, +Δh) & (-Δw, -Δt, -Δh). Moreover, if there must be only one condition each for the best- and worst-case delays, they are (+Δw, +Δt, +Δh) & (-Δw, -Δt, -Δh).