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Monte Carlo Analysis
Statistical Variations on Binning Parameters
Statistical Variations on Binning Parameters
Eldo takes into account changes in binning parameters (for example LMIN, LMAX) due to
Monte Carlo variations. Eldo will first make the variations on the .MODEL, and then select the
appropriate model at each Monte Carlo run. For example:
.PARAM P1=1 DEV=5%
.MODEL N.1 NMOS LMIN='1U*P1' LMAX = '2U*P1'
.MODEL N.2 NMOS LMIN='2U*P1' LMAX='3U*P1'
M1 D G S B N W=1U L=1U
Here Eldo will extract a new random value for P1. This value will be used to update parameters
of both N.1 and N.2. When all parameters of the .MODEL have been updated, Eldo will select
the appropriate model to be used for device M1.
If both the size of a device and the binning parameters of its model are altered by Monte Carlo
variations, Eldo will issue an error that it cannot handle this situation.
Use .OPTION MC_IGNORE_BINNING to disable this automatic selection of the binning
parameters at run time; the model selected at the nominal run will then be used for the whole
Monte Carlo process.
Tip
See .PARAM, .MODEL, and .OPTION MC_IGNORE_BINNING in the Eldo Reference
Manual.
Related Topics
Specifying Statistical Variations for Individual Model Parameters
Assigning Statistical Variations using the .MCMOD Command
Assigning Statistical Variations using the .MCMOD
Command
Modifying the .MODEL lines for the Monte Carlo analysis may not be convenient.
Alternatively, use the .MCMOD command to assign statistical variations for .MODEL
parameters without changing any part of the .MODEL statement.
.MCMOD MODEL_NAME [(LIST_OF_INSTANCES)]
+ PARAM1_NAME LOT|DEV=VALUE [PARAM2_NAME LOT|DEV=VALUE ...}]
The .MODEL name must be specified, followed by one or more pairs of parameters and LOT
and/or DEV values. Optionally, specifying a list of instances will apply the Monte Carlo
probabilities to only instances in that list.
Using the example above, the Monte Carlo parameter may be written as:
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Eldo® User's Manual, 15.3