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Design Languages >> Verilog-AMS >> montecarlo modelling example!!
https://designers-guide.org/forum/YaBB.pl?num=1087364105

Message started by vikas on Jun 15^th, 2004, 10:35pm

Title: montecarlo modelling example!!
Post by vikas on Jun 15^th, 2004, 10:35pm

Hello Ken,

In your article you have talked about some spread (sigma). Is it the variance or mean value?

Also when you define gaussian distribution to a process parameter,is this the variance or mean value(distribution)?

All this correlation coefficient and parameter variation are known to only foundary people,So do they provide it with the model file ?

Regards,
--Vikas

Title: Re: montecarlo modelling example!!
Post by Andrew Beckett on Jun 16^th, 2004, 2:38pm

I assume you're talking about Don O'Riordan's note
http://www.designers-guide.com/Modeling/montecarlo.pdf?

If so, sigma is standard deviation. Process distributions consist of both a mean value and a standard deviation of course.

I'm not really sure what (if anything) you're asking.

In general, this information needs to be provided by the process foundry. Ideally they would provide statistics blocks with the model files, but it doesn't always happen...

Regards,

Andrew.

Title: Re: montecarlo modelling example!!
Post by Andrew Beckett on Jun 16^th, 2004, 2:38pm

Title: Re: montecarlo modelling example!!
Post by Andrew Beckett on Jun 16^th, 2004, 2:39pm

Apologies for the double post - I got a server error part way through posting, and re-posted before I checked to see if it had posted already :'(

Title: Re: montecarlo modelling example!!
Post by vikas on Jun 17^th, 2004, 9:36am

Thanks Andrew,yes it is Don's article not Ken's.

I would like some more clarification of your reply to topic
"monte carlo mismatch simulation in spectre "@
http://www.designers-guide.com/Forum/?board=circuit;action=display;num=1074804759

Here i am facing the same problem(no mismatch variation) and i do'nt really understand "surrounding the parameterized model".
Can you please put more light on this?

Regards,
--Vikas

Title: Re: montecarlo modelling example!!
Post by Andrew Beckett on Jun 21^st, 2004, 3:54pm

Hi Vikas,

This is quite clearly outlined in Don's paper. You need to make sure you have something like this:

Code:

inline subckt mynmos d g s b
parameters w=1u l=1u ad as pd ps ...
mynmos (d g s b) mynmosMod w=w l=l ad=ad ...

// parameterised model
model mynmosMod bsim3v3 type=n param1=value1 param2=value3 ...

ends mynmos

The idea is that you presumably have some parameterised model, with a statistics block describing the std deviation and distribution type of the parameters referred to in the model. What you then do is surround this with a subckt definition (it doesn't have to be inline; that just helps with backannotation), and then you can use the "model" mynmos wherever you like, as if it were a model. Because the real model (mynmosInt) is a parameterised model within a subckt, each instance has its own model, and so they will not be shared. If all instances are shared, you can't have mismatch - whereas if all models are unique to the instance, they can have mismatch.

Does that help?

Regards,

Andrew.