eldo_user

Monte Carlo Analysis
Parameter Naming Conventions
.PARAM VARW=AUNIF(0U,0.05U)
.PARAM VARL=AUNIF(0U,0.05U)
.PARAM BIAS=1M
I1 0 1 BIAS
I2 0 2 BIAS
R1 1 0 RESISTOR
R2 2 0 RESISTOR
.MODEL RESISTOR R LEVEL=3 W=3U L=3U RSH=100 DW=VARW DLR=VARL
In this case, Eldo will create the variables PM(VARW,RESISTOR,DW) and
PM(VARL,RESISTOR,DL).
Implicit Rules of Inheritance
It is possible to define global and local variations by using implicit rules of inheritance.
Consider the following netlist:
.PARAM VAR=AUNIF(3U,0.05U)
.PARAM VARW=AUNIF(VAR,0.01U)
.PARAM BIAS=1M
I1 0 1 BIAS
I2 0 2 BIAS
R1 1 0 RESISTOR W=VARW L=3U
R2 2 0 RESISTOR W=VARW L=3U
.MODEL RESISTOR R LEVEL=3 W=3U L=3U RSH=100
Where we have VARW=AUNIF(VAR,0.05U), a reference to the statistical parameter VAR is
used in the definition of the distribution associated to VARW. In other words, VARW is the
sum VAR + AUNIF(0,0.01U); the distribution of VARW is the sum of two random variables.
In this example, there are three random variables:
• PP(VAR,VARW) the random variable with global variations.
• PE(VARW,R1,W) and PE(VARW,R2,W) the local random variables.
The VARW parameter does not inherit the DEV variations of VAR. During the Monte Carlo
sampling, a value for PP(VAR,VARW) is drawn from the uniform distribution
AUNIF(3U,0.05U) and two independent values PE(VARW,R1,W) and PE(VARW,R2,W) are
obtained from the uniform distribution AUNIF(0,0.01U). The final values of the width W in R1
and R2 are therefore computed by summing these random values to PP(VAR,VARW).
Note that this behavior cannot be obtained with following statements:
.PARAM VAR1=AUNIF(0,0.05U)
.PARAM VAR2=AUNIF(0,0.01U)
.PARAM VARW=’3U + VAR1 + VAR2’
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Eldo® User's Manual, 15.3