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.

    Importance sampling method for multiple failure regions

    公开(公告)号:US10330727B2

    公开(公告)日:2019-06-25

    申请号:US15365808

    申请日:2016-11-30

    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.

    SYSTEM AND METHOD FOR CIRCUIT SIMULATION BASED ON RECURRENT NEURAL NETWORKS

    公开(公告)号:US20190138897A1

    公开(公告)日:2019-05-09

    申请号:US15951052

    申请日:2018-04-11

    Abstract: According to one embodiment of the present invention a circuit simulator configured to simulate a degraded output of a circuit including a plurality of transistors includes: a behavioral recurrent neural network configured to receive an input waveform and to compute a circuit output waveform; a feature engine configured to model one or more degraded circuit elements in accordance with an aging time, to receive the circuit output waveform and to output a plurality of degraded features; and a physics recurrent neural network configured to receive the plurality of degraded features from the feature engine and to simulate the degraded output of the circuit.

    Systems, methods and computer program products for analyzing performance of semiconductor devices

    公开(公告)号:US10204188B2

    公开(公告)日:2019-02-12

    申请号:US14991124

    申请日:2016-01-08

    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.

    Method for transistor design with considerations of process, voltage and temperature variations

    公开(公告)号:US10146896B2

    公开(公告)日:2018-12-04

    申请号:US15344346

    申请日:2016-11-04

    Abstract: A method for selecting transistor design parameters. A first set of simulations is used to calculate leakage current at a plurality of sets of design parameter values, and the results are fitted with a first response surface methodology model. The first model is used to generate a function that returns a value of a selected design parameter, for which a leakage current specification is just met. A second set of simulations is used to calculate effective drive current for a plurality of sets of design parameter values, and the results are fitted with a second response surface methodology model. The second model is used, together with the first, to search for a set of design parameter values at which a worst-case effective drive current is greatest, subject to the constraint of meeting the worst-case leakage current specification.

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