High performance circuits are facing increasingly severe signal integrity problems due to crosstalk noise and crosstalk noise awareness has become an integral part of static timing analysis (STA). Existing crosstalk noise aware STA methods compute noise induced delay uncertainty on a net by net basis and in a pessimistic way, without considering the overlap bounds of the victim and aggressor timing windows and realistic delay impact on early and late signal arrival times. Since crosstalk induced delay on individual nets contribute cumulatively on data and clock paths, even small amounts of pessimism in computation can add up to produce several unrealistic timing violations. Unlike glitch noise analysis where noise often attenuates during propagation, quality of delay noise analysis is severely affected by any pessimism in noise estimation and can unnecessarily cost valuable silicon and design resources for fixing unreal violations. In this paper, we propose two temporal techniques to reduce pessimism in crosstalk noise aware STA. The first method, "effective delay noise", is a net based method where the exact overlap points of victim and aggressor timing windows are considered to obtain the part of delay noise that actually impacts early and late signal arrival times. The second method, "path based delay noise", is a path based method where the reduced arrival uncertainty of the nets of a given path are utilized for pessimism reduction. We also propose a novel "uncertainty propagation" technique as part of the second method, which results in an iteration free crosstalk noise aware STA of the path with significantly reduced pessimism. The two techniques are combined in a proposed methodology that is compatible with existing industrial static timing analyzers with very little computational overhead compared to the traditional noise aware STA and a significant improvement in eliminating unreal violations. The proposed techniques resulted in 77% reduction of worst case negative slack and 57% reduction in the number of failing paths in the setup analysis of a 90nm industrial design.

Noise analysis has become a critical concern in advanced chip designs. Traditional methods suffer from two common issues. First, noise that is propagated through the driver of a net is combined with noise injected by capacitively coupled aggressor nets using linear summation. Since this ignores the non-linear behavior of the driver gate the noise that develops on a net can be significantly underestimated. We therefore propose a new linear model that accurately combines propagated and injected noise on a net and which maintains the efficiency of linear simulation. After the propagated and injected noise are correctly combined on a victim net, it is necessary to determine if the noise can result in a functional failure. This is the second issue that we discuss in this paper. Traditionally, noise failure criteria have been based on unity gain points of the DC or AC transfer curves. However, we will show that for digital designs, these approaches can result in a pessimistic analysis in some cases, while in other cases, they allow circuit operation that is extremely close to regions that are unstable and do not allow sufficient margin for error in the analysis. In this paper, we compare the effectiveness of the discussed noise failure criteria and also present a propagation based method, which is intended to overcome these drawbacks. The proposed methods were implemented in a noise analysis tool and we demonstrate results on industrial circuits.

In this paper, we present a new approach to model the impact of cross-coupling noise on interconnect delay. We introduce a new linear driver model that accurately models the noise pulse induced on a switching signal net due to cross coupling capacitance. The proposed model effectively captures the non-linear behavior of the victim driver gate during the transition and has an average error below 8% whereas the traditional approach using a Thevenin model incurs an average error of 48%. We also discuss the worst case alignment of the aggressor net transitions with respect to the victim net transition, emphasizing the need to maximize not merely the delay of the interconnect alone but the combined delay of the interconnect and receiver gate. We show that the worst case alignment of an aggressor net transition is a function of the receiver gate output loading, victim transition edge rate, and the noise pulse width and height and hence propose a pre-characterization approach to efficiently predict the worst-case alignment. The proposed methods were implemented in an industrial noise analysis tool called ClariNet. Results on industrial designs are presented to demonstrate the effectiveness of our approach.

Coupled noise analysis has become a critical issue for deep-submicron, high performance design. In this paper, we present, ClariNet, an industrial noise analysis tool, which was developed to efficiently analyze large, high performance processor designs. We present the overall approach and tool flow of ClariNet and discuss three critical large-processor design issues which have received limited discussion in the past. First, we present how the driver gates of a coupled interconnect network are represented with accurate linear models. Second, we show how to speed the analysis of large designs by using noise filters based on reduced interconnect representations and then pruning the nets coupled to a signal net. Third, we show how to incorporate logic and timing correlations into noise analysis to reduce its pessimism. We present the results from several industrial circuits, including a large high performance microprocessor design and a DSP design.