SRAM circuit yield analysis method based on non-Gaussian sampling

Abstract

The invention belongs to the field of static random access memory circuit yield analysis in integrated circuit manufacturability design, and particularly relates to a method for obtaining an optimal actual sampling distribution parameter by adopting general Pareto and Gaussian joint distribution as an actual sampling distribution function family and minimizing cross entropy between actual samplingdistribution and ideal sampling distribution. The optimized actual sampling distribution is used for sampling and calculating the SRAM failure rate, so that the number of sampling points can be greatly reduced, and the sampling efficiency is improved. The key point of the invention lies in that general Pareto and Gaussian mixture distribution is adopted as a sampling distribution function family;aiming at the distributed parameter optimization problem, an iteration strategy is provided, sampling is continuously carried out, actual distribution parameters are updated, and the failure rate iscalculated until the failure rate meets the precision requirement. Experimental results show that the method provided by the invention is obviously superior to a method in the prior art.

Description

technical field [0001] The invention belongs to the field of Static Random Access Memory (SRAM) circuit yield analysis in integrated circuit manufacturability design, and specifically relates to a non-Gaussian sampling-based SRAM circuit yield analysis method. Background technique [0002] It is disclosed in the prior art that as the dimensions of semiconductor manufacturing processes continue to shrink, the influence of process disturbances on the performance and reliability of SRAM circuits becomes more and more significant. In order to reduce chip area, SRAM cells are often designed with the smallest process size, which makes their performance easily affected by process disturbances. At the same time, practice shows that a large number of repeated SRAM cells are included in an SRAM circuit. In order to ensure the yield rate of the overall SRAM circuit, the failure rate of each SRAM cell must be extremely low (generally should be lower than 10 -6 ). [0003] Generally, t...

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Problems solved by technology

However μ * The initial value starts from 0, which makes the number of iterations too many, resulting in a waste of sampling points

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