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Monte Carlo Analysis<br />

Obsolete Features<br />

.PARAM TOX=19E-09<br />

.PARAM TOX_GLOB =TOX<br />

LOT/GAUSS=2%<br />

.SUBCKT N D G S B PARAM: W=1U L=1U<br />

M1 D G S B MODN W=W L=L<br />

.PARAM A_MM_TOX=0.4543U B_MM_TOX=0.1435<br />

+ DEV_MM_TOX =’A_MM_TOX/SQRT(W*L)+B_MM_TOX’<br />

.PARAM VTH0=.3322 A_MM_VTH0=0.40654U B_MM_VTH0=0.11654<br />

+ DEV_MM_VTH0 =’A_MM_VTH0/SQRT(W*L)+B_MM_VTH0’<br />

.PARAM U0=388.3203 A_MM_U0=0.565745U B_MM_U0=0.264563<br />

+ DEV_MM_U0 =’A_MM_U0/SQRT(W*L)+B_MM_U0’<br />

.MODEL MODN NMOS<br />

+LEVEL=53<br />

+TOX = TOX_GLOB DEV/GAUSS={DEV_MM_TOX}%<br />

+VTH0 = VTH0 DEV/GAUSS={DEV_MM_VTH0}%<br />

+U0 = U0 DEV/GAUSS={DEV_MM_U0}%<br />

+KF=1E-27 AF=2<br />

+TNOM=27.0<br />

...<br />

.ENDS<br />

Outside the .SUBCKT block we created the parameter TOX_GLOB with explicit LOT<br />

variations. This results in the generation of a random variable named P(TOX_GLOB). Finally<br />

we will have 52 independent variables.<br />

Related Topics<br />

Statistical Variations<br />

Obsolete Features<br />

The features described here are related to sampling methods, not statistical models, and should<br />

not be used.<br />

LIMIT Distribution<br />

The LIMIT distribution is a discrete probability distribution on finite set {L, U} which can be<br />

characterized by saying that the values L and U are equally probable.<br />

548<br />

Eldo® User's Manual, 15.3

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