S
spectrallypure
Guest
Hello all! I am trying to understand the differences between the two
major types of montecarlo analysis that can be run in Cadence (process-
only and mismatch-only) , but I am having trouble trying to interpret
their definitions with respect to the actual results they predict.
I am simulating a very simple dynamic circuit, consisting of a
differential pair whose output currents are used to charge identical
capacitors. The variable of interest is the differential voltage
accross the capacitors after a certain integration time. I am running
monte carlo simulations CONSIDERING ONLY the statistical variations in
MOS transistors (not in the capacitors). I have run both types of
monte carlo simulations twice: first with nominal gate sizes and then
a second time doubling both gate dimensions in order to quadruplicate
the area. The results are as follows; the measured quantity is the
deviation (spread) from the nominal differential output voltage that
is expected:
Version 1) Diff. pair with dimensions L1, W1 (A1=W1.L1):
-Mismatch-only simulation: Spread(Vout,diff) = 20mV approx.
-Process-only simulation: Spread(Vout,diff) = 100mV approx.
Version 2) Diff. pair with dimensions L2=2L1, W2=2W1(A2=4A1):
-Mismatch-only simulation: Spread(Vout,diff) = 10mV approx.
-Process-only simulation: Spread(Vout,diff) = 100mV approx.
As expected, the spread in the differential output voltage is halved
by a four-fold in the gate area. However, in both cases the "process"
variations overwhelm the "mismatch" variations. What's worse, these
process variations don't seem to improve at all by increasing the
transistor areas!!! :O
The questions are, then,
-If I were to manufacture both versions of this circuit tomorrow,
what would be the (worst-case) expected spreads in the output voltage
that I would get? 10 and 20mV, respectively? 100mV in both cases?
neither?
-How in the world can I reduce the "process variations" through
design? Are these variations something that the designer can combat-
with, or rather live-with?
Sorry if this all is a little off-topic; I really look forward to hear
what is the generalized undestanding about the practical results of
monte carlo analysis, and what the experienced folks would do in this
situation.
Thanks in advance for any ideas!
Cheers,
Jorge.
major types of montecarlo analysis that can be run in Cadence (process-
only and mismatch-only) , but I am having trouble trying to interpret
their definitions with respect to the actual results they predict.
I am simulating a very simple dynamic circuit, consisting of a
differential pair whose output currents are used to charge identical
capacitors. The variable of interest is the differential voltage
accross the capacitors after a certain integration time. I am running
monte carlo simulations CONSIDERING ONLY the statistical variations in
MOS transistors (not in the capacitors). I have run both types of
monte carlo simulations twice: first with nominal gate sizes and then
a second time doubling both gate dimensions in order to quadruplicate
the area. The results are as follows; the measured quantity is the
deviation (spread) from the nominal differential output voltage that
is expected:
Version 1) Diff. pair with dimensions L1, W1 (A1=W1.L1):
-Mismatch-only simulation: Spread(Vout,diff) = 20mV approx.
-Process-only simulation: Spread(Vout,diff) = 100mV approx.
Version 2) Diff. pair with dimensions L2=2L1, W2=2W1(A2=4A1):
-Mismatch-only simulation: Spread(Vout,diff) = 10mV approx.
-Process-only simulation: Spread(Vout,diff) = 100mV approx.
As expected, the spread in the differential output voltage is halved
by a four-fold in the gate area. However, in both cases the "process"
variations overwhelm the "mismatch" variations. What's worse, these
process variations don't seem to improve at all by increasing the
transistor areas!!! :O
The questions are, then,
-If I were to manufacture both versions of this circuit tomorrow,
what would be the (worst-case) expected spreads in the output voltage
that I would get? 10 and 20mV, respectively? 100mV in both cases?
neither?
-How in the world can I reduce the "process variations" through
design? Are these variations something that the designer can combat-
with, or rather live-with?
Sorry if this all is a little off-topic; I really look forward to hear
what is the generalized undestanding about the practical results of
monte carlo analysis, and what the experienced folks would do in this
situation.
Thanks in advance for any ideas!
Cheers,
Jorge.