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Perform Monte Carlo simulation in ngspice
* 25 stage Ring-Osc. BSIM3 with statistical variation of various model parameters
* cd into ngspice/examples/Monte_Carlo
* start in interactive mode 'ngspice MC_ring.sp' with several plots for output
* or start in batch mode, controlled by .control section (Control mode)
* with 'ngspice -b -r MC_ring.raw -o MC_ring.log MC_ring.sp'.
vin in out dc 0.5 pulse 0.5 0 0.1n 5n 1 1 1
vdd dd 0 dc 3.3
vss ss 0 dc 0
ve sub 0 dc 0
vpe well 0 dc 3.3
.subckt inv1 dd ss sub well in out
mn1 out in ss sub n1 w=2u l=0.35u as=3p ad=3p ps=4u pd=4u
mp1 out in dd well p1 w=4u l=0.35u as=7p ad=7p ps=6u pd=6u
.ends inv1
.subckt inv5 dd ss sub well in out
xinv1 dd ss sub well in 1 inv1
xinv2 dd ss sub well 1 2 inv1
xinv3 dd ss sub well 2 3 inv1
xinv4 dd ss sub well 3 4 inv1
xinv5 dd ss sub well 4 out inv1
.ends inv5
xinv1 dd ss sub well in out5 inv5
xinv2 dd ss sub well out5 out10 inv5
xinv3 dd ss sub well out10 out15 inv5
xinv4 dd ss sub well out15 out20 inv5
xinv5 dd ss sub well out20 out inv5
xinv11 dd 0 sub well out buf inv1
cout buf ss 0.2pF
*
.options noacct
.control
save buf $ we just need buf, save memory by more than 10x
let mc_runs = 30 $ number of runs for monte carlo
let run = 0 $ number of actual run
set curplot = new $ create a new plot
set curplottitle = "Transient outputs"
set plot_out = $curplot $ store its name to 'plot_out'
set curplot = new $ create a new plot
set curplottitle = "FFT outputs"
set plot_fft = $curplot $ store its name to 'plot_fft'
set curplot = new $ create a new plot
set curplottitle = "Oscillation frequency"
set max_fft = $curplot $ store its name to 'max_fft'
let mc_runsp = mc_runs + 1
let maxffts = unitvec(mc_runsp) $ vector for storing max measure results
let halfffts = unitvec(mc_runsp)$ vector for storing measure results at -40dB rising
*
* define distributions for random numbers:
* unif: uniform distribution, deviation relativ to nominal value
* aunif: uniform distribution, deviation absolut
* gauss: Gaussian distribution, deviation relativ to nominal value
* agauss: Gaussian distribution, deviation absolut
define unif(nom, var) (nom + (nom*var) * sunif(0))
define aunif(nom, avar) (nom + avar * sunif(0))
define gauss(nom, var, sig) (nom + (nom*var)/sig * sgauss(0))
define agauss(nom, avar, sig) (nom + avar/sig * sgauss(0))
*
* We want to vary the model parameters vth0, u0, tox, lint, and wint
* of the BSIM3 model for the NMOS and PMOS transistors.
* We may obtain the nominal values (nom) by manually extracting them from
* the parameter set. Here we get them automatically and store them into
* vectors. This has the advantage that you may change the parameter set
* without having to look up the values again.
let n1vth0=@n1[vth0]
let n1u0=@n1[u0]
let n1tox=@n1[tox]
let n1lint=@n1[lint]
let n1wint=@n1[wint]
let p1vth0=@p1[vth0]
let p1u0=@p1[u0]
let p1tox=@p1[tox]
let p1lint=@p1[lint]
let p1wint=@p1[wint]
*
* run the simulation loop
dowhile run <= mc_runs
* run=0 simulates with nominal parameters
if run > 0
setplot $max_fft
altermod @n1[vth0] = gauss(n1vth0, 0.1, 3)
altermod @n1[u0] = gauss(n1u0, 0.05, 3)
altermod @n1[tox] = gauss(n1tox, 0.1, 3)
altermod @n1[lint] = gauss(n1lint, 0.1, 3)
altermod @n1[wint] = gauss(n1wint, 0.1, 3)
altermod @p1[vth0] = gauss(p1vth0, 0.1, 3)
altermod @p1[u0] = gauss(p1u0, 0.1, 3)
altermod @p1[tox] = gauss(p1tox, 0.1, 3 )
altermod @p1[lint] = gauss(p1lint, 0.1, 3)
altermod @p1[wint] = gauss(p1wint, 0.1, 3)
end
tran 15p 100n 0
* select stop and step so that number of data points after linearization is not too
* close to 8192, which would yield varying number of line length and thus scale for fft.
*
* We have to figure out what to do if a single simulation will not converge.
* There is the variable 'sim_status' which is set to 1 if the simulation
* fails with ’xx simulation(s) aborted’, e.g. because of non-convergence.
* Then we might skip this run and continue with a new run.
*
echo Simulation status $sim_status
let simstat = $sim_status
if simstat = 1
if run = mc_runs
echo go to end
else
echo go to next run
end
destroy $curplot
goto next
end
set run ="$&run" $ create a variable from the vector
set mc_runs ="$&mc_runs" $ create a variable from the vector
echo simulation run no. $run of $mc_runs
set dt = $curplot
* save the linearized data for having equal time scales for all runs
linearize buf $ linearize only buf, no other vectors needed
destroy $dt $ delete the tran i plot
set dt = $curplot $ store the current plot to dt (tran i+1)
setplot $plot_out $ make 'plt_out' the active plot
* firstly save the time scale once to become the default scale
if run=0
let time={$dt}.time
end
let vout{$run}={$dt}.buf $ store the output vector to plot 'plot_out'
setplot $dt $ go back to the previous plot (tran i+1)
fft buf $ run fft on vector buf
destroy $dt $ delete the tran i+1 plot
let buf2=db(mag(buf))
* find the frequency where buf has its maximum of the fft signal
meas sp fft_max MAX_AT buf2 from=0.1G to=0.7G
* find the frequency where buf is -40dB at rising fft signal
meas sp fft_40 WHEN buf2=-40 RISE=1 from=0.1G to=0.7G
echo
echo
* store the fft vector
set dt = $curplot $ store the current plot to dt (spec i)
setplot $plot_fft $ make 'plot_fft' the active plot
if run=0
let frequency={$dt}.frequency
end
let fft{$run}={$dt}.buf $ store the output vector to plot 'plot_fft'
* store the measured value
setplot $max_fft $ make 'max_fft' the active plot
let maxffts[{$run}]={$dt}.fft_max
let halfffts[{$run}]={$dt}.fft_40
let run = run + 1
label next
reset
end
***** plotting **********************************************************
if $?batchmode
echo
echo Plotting not available in batch mode
echo Write linearized vout0 to vout{$mc_runs} to rawfile $rawfile
echo
write $rawfile {$plot_out}.allv
rusage
quit
else
setplot $plot_out
plot vout0 ylabel 'RO output, original parameters' $ just plot the tran output with nominal parameters
setplot $plot_fft
settype decibel ally
plot db(mag(ally)) xlimit .1G 1G ylimit -80 10 ylabel 'fft output'
*
* create a histogram from vector maxffts
setplot $max_fft $ make 'max_fft' the active plot
set startfreq=400MEG
set bin_size=5MEG
set bin_count=20
compose xvec start=$startfreq step=$bin_size lin=$bin_count $ requires variables as parameters
settype frequency xvec
let bin_count=$bin_count $ create a vector from the variable
let yvec=unitvec(bin_count) $ requires vector as parameter
let startfreq=$startfreq
let bin_size=$bin_size
* put data into the correct bins
let run = 0
dowhile run < mc_runs
set run = $&run $ create a variable from the vector
let val = maxffts[{$run}]
let part = 0
* Check if val fits into a bin. If yes, raise bin by 1
dowhile part < bin_count
if ((val < (startfreq + (part+1)*bin_size)) & (val > (startfreq + part*bin_size)))
let yvec[part] = yvec[part] + 1
break
end
let part = part + 1
end
let run = run + 1
end
* plot the histogram
set plotstyle=combplot
plot yvec-1 vs xvec xlabel 'oscillation frequency' ylabel 'bin count' $ subtract 1 because we started with unitvec containing ones
* plot simulation series
set plotstyle=linplot
let xx = vector(mc_runsp)
settype frequency maxffts
plot maxffts vs xx xlabel 'iteration no.' ylabel 'RO frequency'
* calculate jitter
let diff40 = (vecmax(halfffts) - vecmin(halfffts))*1e-6
echo
echo Max. jitter is "$&diff40" MHz
end
rusage
.endc
********************************************************************************
.model n1 nmos
+level=8
+version=3.3.0
+tnom=27.0
+nch=2.498e+17 tox=9e-09 xj=1.00000e-07
+lint=9.36e-8 wint=1.47e-7
+vth0=.6322 k1=.756 k2=-3.83e-2 k3=-2.612
+dvt0=2.812 dvt1=0.462 dvt2=-9.17e-2
+nlx=3.52291e-08 w0=1.163e-6
+k3b=2.233
+vsat=86301.58 ua=6.47e-9 ub=4.23e-18 uc=-4.706281e-11
+rdsw=650 u0=388.3203 wr=1
+a0=.3496967 ags=.1 b0=0.546 b1=1
+dwg=-6.0e-09 dwb=-3.56e-09 prwb=-.213
+keta=-3.605872e-02 a1=2.778747e-02 a2=.9
+voff=-6.735529e-02 nfactor=1.139926 cit=1.622527e-04
+cdsc=-2.147181e-05
+cdscb=0 dvt0w=0 dvt1w=0 dvt2w=0
+cdscd=0 prwg=0
+eta0=1.0281729e-02 etab=-5.042203e-03
+dsub=.31871233
+pclm=1.114846 pdiblc1=2.45357e-03 pdiblc2=6.406289e-03
+drout=.31871233 pscbe1=5000000 pscbe2=5e-09 pdiblcb=-.234
+pvag=0 delta=0.01
+wl=0 ww=-1.420242e-09 wwl=0
+wln=0 wwn=.2613948 ll=1.300902e-10
+lw=0 lwl=0 lln=.316394 lwn=0
+kt1=-.3 kt2=-.051
+at=22400
+ute=-1.48
+ua1=3.31e-10 ub1=2.61e-19 uc1=-3.42e-10
+kt1l=0 prt=764.3
+noimod=2
+af=1.075e+00 kf=9.670e-28 ef=1.056e+00
+noia=1.130e+20 noib=7.530e+04 noic=-8.950e-13
**** PMOS ***
.model p1 pmos
+level=8
+version=3.3.0
+tnom=27.0
+nch=3.533024e+17 tox=9e-09 xj=1.00000e-07
+lint=6.23e-8 wint=1.22e-7
+vth0=-.6732829 k1=.8362093 k2=-8.606622e-02 k3=1.82
+dvt0=1.903801 dvt1=.5333922 dvt2=-.1862677
+nlx=1.28e-8 w0=2.1e-6
+k3b=-0.24 prwg=-0.001 prwb=-0.323
+vsat=103503.2 ua=1.39995e-09 ub=1.e-19 uc=-2.73e-11
+rdsw=460 u0=138.7609
+a0=.4716551 ags=0.12
+keta=-1.871516e-03 a1=.3417965 a2=0.83
+voff=-.074182 nfactor=1.54389 cit=-1.015667e-03
+cdsc=8.937517e-04
+cdscb=1.45e-4 cdscd=1.04e-4
+dvt0w=0.232 dvt1w=4.5e6 dvt2w=-0.0023
+eta0=6.024776e-02 etab=-4.64593e-03
+dsub=.23222404
+pclm=.989 pdiblc1=2.07418e-02 pdiblc2=1.33813e-3
+drout=.3222404 pscbe1=118000 pscbe2=1e-09
+pvag=0
+kt1=-0.25 kt2=-0.032 prt=64.5
+at=33000
+ute=-1.5
+ua1=4.312e-9 ub1=6.65e-19 uc1=0
+kt1l=0
+noimod=2
+af=9.970e-01 kf=2.080e-29 ef=1.015e+00
+noia=1.480e+18 noib=3.320e+03 noic=1.770e-13
.end
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