SYSTEM AND METHOD FOR COMPACT NEURAL NETWORK MODELING OF TRANSISTORS

    公开(公告)号:US20200320366A1

    公开(公告)日:2020-10-08

    申请号:US16430219

    申请日:2019-06-03

    Abstract: A method for generating a model of a transistor includes: initializing hyper-parameters; training the neural network in accordance with the hyper-parameters and training data relating transistor input state values to transistor output state values to compute neural network parameters; determining whether the transistor output state values of the training data match an output of the neural network; porting the neural network to a circuit simulation code to generate a ported neural network; simulating a test circuit using the ported neural network to simulate behavior of a transistor of the test circuit to generate simulation output; determining whether a turnaround time of the generation of the simulation output is satisfactory; in response to determining that the turnaround time is unsatisfactory, re-training the neural network based on updated hyper-parameters; and in response to determining that the turnaround time is satisfactory, outputting the ported neural network as the model of the transistor.

    IMPORTANCE SAMPLING METHOD FOR MULTIPLE FAILURE REGIONS

    公开(公告)号:US20190265296A1

    公开(公告)日:2019-08-29

    申请号:US16406868

    申请日:2019-05-08

    Abstract: In a method of circuit yield analysis, the method includes: detecting a plurality of failed samples respectively located at a plurality of failure regions in a multi-dimensional parametric space; clustering the failed samples to identify the failure regions; filtering features of the failed samples to determine a parameter component that is a non-principal component in affecting circuit yield; applying a dimensional reduction method on a dimension corresponding to the parameter component; and constructing a final importance sampling (IS) distribution function using a mixed Gaussian (mGaussian) function corresponding to all of the failure regions containing a rare failure event.

    IMPORTANCE SAMPLING METHOD FOR MULTIPLE FAILURE REGIONS

    公开(公告)号:US20180074124A1

    公开(公告)日:2018-03-15

    申请号:US15365808

    申请日:2016-11-30

    CPC classification number: G01R31/31718 G01R31/2894 G01R31/3177

    Abstract: A method of circuit yield analysis for evaluating rare failure events existing in multiple disjoint failure regions defined by a multi-dimensional parametric space, the method including performing initial sampling to detect failed samples respectively located at multiple failure regions in the multi-dimensional parametric space, performing clustering to identify the failure regions, performing feature filtering to determine which parameter component is a non-principal component in affecting circuit yield, applying a dimensional reduction method on a dimension corresponding to the parameter component, optimizing an importance sampling (IS) distribution function corresponding to each of the failure regions, and constructing a final importance sampling (IS) distribution function using a mixed Gaussian (mGaussian) function corresponding to all of the failure regions.

    GENERIC HIGH-DIMENSIONAL IMPORTANCE SAMPLING METHODOLOGY

    公开(公告)号:US20180300288A1

    公开(公告)日:2018-10-18

    申请号:US15696150

    申请日:2017-09-05

    Abstract: A method of circuit yield analysis for evaluating rare failure events includes performing initial sampling to detect failed samples respectively located at one or more failure regions in a multi-dimensional parametric space, generating a distribution of failed samples at discrete values along each dimension, identifying the failed samples, performing a transform to project the failed samples into all dimensions in a transform space, and classifying a type of failure region for each dimension in the parametric space.

    Systems, Methods and Computer Program Products for Analyzing Performance of Semiconductor Devices
    19.
    发明申请
    Systems, Methods and Computer Program Products for Analyzing Performance of Semiconductor Devices 审中-公开
    用于分析半导体器件性能的系统,方法和计算机程序产品

    公开(公告)号:US20160267205A1

    公开(公告)日:2016-09-15

    申请号:US14991124

    申请日:2016-01-08

    CPC classification number: G06F17/5009 G06F17/5036 G06F17/5081 G06F2217/10

    Abstract: A computer implemented method for determining performance of a semiconductor device is provided. The method includes providing a technology computer aided design data set corresponding to nominal performance of the semiconductor device, identifying a plurality of process variation sources that correspond to process variations that occur during the manufacturing of the semiconductor device, generating a nominal value look-up table of electrical parameters of the semiconductor device using nominal values of each of the plurality of process variation sources, and generating a plurality of process variation look-up tables of electrical parameters of the semiconductor device using variation values corresponding to each of the plurality of process variation sources that are identified as corresponding to the semiconductor device.

    Abstract translation: 提供了一种用于确定半导体器件性能的计算机实现方法。 该方法包括提供对应于半导体器件的标称性能的技术计算机辅助设计数据集,识别对应于在制造半导体器件期间发生的工艺变化的多个工艺变化源,产生标称值查找表 使用所述多个处理变化源中的每一个的标称值来使用所述半导体器件的电参数,以及使用对应于所述多个工艺变化中的每一个的变化值来生成所述半导体器件的电参数的多个工艺变化查找表 被识别为对应于半导体器件的源。

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