;As devices continue to shrink, the process variation and aging effects have increasing impacts on the circuit yield and reliability, particularly for analog circuits. If those non-ideal effects can be considered in early design stages, the re-design and re-spin costs can be significantly reduced. Traditional simulation-based methods to deal with the problems can achieve a high accuracy, but the simulation cost is very expensive. Thus, a new simulation-based analysis method that considers the process variation and aging effects is proposed, which can keep the cost at a reasonable scale while maintaining high accuracy.
First, the delta circuit model is improved with a set of basic delta devices for circuit simulation. By using the delta circuit model, simulation speed can be improved automatically due to the dynamic step control in transient analysis. In order to further improve the efficiency while combining the delta circuit model and QMC sampling, a cluster-based delta-QMC technique is proposed in this dissertation to reduce the delta change in each sample. Experimental results indicate that the proposed approach can increase simulation speed by two orders of magnitude with almost the same accuracy, which significantly improves the efficiency of yield analysis.
Second, an incremental simulation technique based on delta model is proposed to improve the simulation speed of lifetime yield analysis while maintaining the analysis accuracy. Because aging is often a gradual process, the proposed incremental technique is effective for reducing the simulation time. For yield analysis with degraded performance, this incremental technique also reduces the simulation time because each sample is the same circuit with small parameter changes in the Monte Carlo analysis. When the proposed dynamic aging sampling technique is employed, 50X speedup can be obtained with maximum estimation error of 1%, which considerably improves the efficiency of lifetime yield analysis.
