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Montecarlo simulation with Verilog-A and Python

farhan89

Hi All,

I have a Verilog-A model of a transistor and now I am extending it for variability modeling. Currently I have a test variability model in Python that uses some libraries to generate results for Montecarlo simulation (using transistor model in python language). Now, I would like to convert the complete model in to Verilog-A compatible format. I have read Verilog-A manual and what I have understood is that I have to write a statistical block to run Montecarlo simulation (by generating samples for each simulation run). For that, I have few questions:

1. Can I call python code from Verilog-A or Statistical block to generate a model parameters sample from my python code and then run simulation using spectre simulator with python generated samples?

2. Can I define Joint PDF (means and co-variances matrix) in statistical block?

I am using Cadence IC 6.1.6 and MMSIM 14.10.

Thanks

Regards,

Farhan

Parents

  • Taking the normal random variables as an example, in spectre you specify a standard deviation and it gives you a zero mean, independently distributed variable.  But you can decompose a set of random variables with different means and a co-variance matrix into sums of independent, zero mean random variables.  I.e.

    y = Ax + b

    where x are your zero mean, unit variance random variables, A is a matrix that transforms to give the desired variances and co-variances, and b is a vector of means. 

    -Dan

Reply

  • Taking the normal random variables as an example, in spectre you specify a standard deviation and it gives you a zero mean, independently distributed variable.  But you can decompose a set of random variables with different means and a co-variance matrix into sums of independent, zero mean random variables.  I.e.

    y = Ax + b

    where x are your zero mean, unit variance random variables, A is a matrix that transforms to give the desired variances and co-variances, and b is a vector of means. 

    -Dan

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