This paper proposes a gate delay model that is suitable for timing analysis considering wide-range process and environmental variability. The proposed model focuses on current variation and its impact on delay is considered by replacing output load. The proposed model is applicable for large variability with current model constructed by DC analysis whose cost is small. The proposed model can also be used both in statistical static timing analysis and in conventional corner-based static timing analysis. Experimental results in a 90nm technology show that the gate delays of inverter, NAND and NOR are accurately estimated under gate length, threshold voltage, supply voltage and temperature fluctuation. We also verify that the proposed model can cope with slow input transition and RC output load. We demonstrate applicability to multiple-stage path delay and flip-flop delay, and show an application of sensitivity calculation for statistical timing analysis.
This paper presents a self-compensation scheme of manufacturing variability for clock skew reduction. In the proposed scheme, a CDN with embedded variability sensors tunes variable clock drivers for canceling the clock skew induced by manufacturing variability. We apply the proposed scheme for a mesh-style CDN in a 65nm technology and evaluate the deskewing effect as a function of the sensor performance. Experimental results show that the skew can be reduced by over 70% and the correlation coefficient between estimated and actual variabilities, which represents the sensor performance, should be more than 0.3 for skew reduction.
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