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ChipNo_list = [11, 12, 13, 14, 15, 16]; | ||
temp_list = -40:10:120; | ||
supply_list = [1.8]; | ||
TZiK = 273.15; scale = 1; | ||
p1 = 5; % 0C | ||
p2 = 13; % 80C | ||
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plim_low = 3; % -20C | ||
plim_high = 15; % 100C | ||
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% Re-organize Measured Data | ||
freq_data_array = zeros(length(temp_list), length(supply_list), length(ChipNo_list), 64); | ||
for c=1:length(ChipNo_list) | ||
for t=1:length(temp_list) | ||
for s=1:length(supply_list) | ||
file = ['../MeasResults/ChipNo', num2str(ChipNo_list(c)), '/Meas_ChipNo', num2str(ChipNo_list(c)), '_Vdio3.0Vdd', num2str(supply_list(s)), '_', num2str(temp_list(t)), 'C.csv']; | ||
dtable = readtable(file, 'PreserveVariableNames', 1); | ||
for design = 1:64 | ||
freq_data_array(t, s, c, design) = table2array(dtable(design, 'Freq0 (kHz)')); | ||
end | ||
end | ||
end | ||
end | ||
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% Fit each node | ||
param_array = zeros(2, length(supply_list), length(ChipNo_list), 64); | ||
T_array = zeros(length(temp_list), length(supply_list), length(ChipNo_list), 64); | ||
T_err_array = zeros(length(temp_list), length(supply_list), length(ChipNo_list), 64); | ||
err_range_array = zeros(4, length(supply_list), length(ChipNo_list), 64); | ||
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for c=1:length(ChipNo_list) | ||
for design = 1:64 | ||
for s = 1:length(supply_list) | ||
freq_list = freq_data_array(:, s, c, design); | ||
k = (temp_list(p2)-temp_list(p1)) / (log(freq_list(p2))*(temp_list(p2) + TZiK)*scale - log(freq_list(p1))*(temp_list(p1) + TZiK)*scale); | ||
b = -k*log(freq_list(p1))*(temp_list(p1) + TZiK)*scale; | ||
param_array(1, s, c, design) = k; param_array(2, s, c, design) = b; | ||
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for t = 1:length(temp_list) | ||
T_array(t, s, c, design) = (scale * TZiK * k * log(freq_list(t)) + b) / (1 - scale * k * log(freq_list(t))); | ||
T_err_array(t, s, c, design) = T_array(t, s, c, design) - temp_list(t); | ||
end | ||
err_range_array(1, s, c, design) = max(T_err_array(plim_low:plim_high, s, c, design)); % largest positive error | ||
err_range_array(2, s, c, design) = min(T_err_array(plim_low:plim_high, s, c, design)); % largest negative error | ||
err_range_array(3, s, c, design) = max(abs(T_err_array(plim_low:plim_high, s, c, design))); % largest absolute error | ||
err_range_array(4, s, c, design) = sum(abs(T_err_array(plim_low:plim_high, s, c, design)))/(plim_high - plim_low + 1 - 2); % mean absolute error | ||
end | ||
end | ||
end | ||
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c = 4; | ||
[max_abs_error_lst, design] = min(err_range_array(3, 1, c, :)); | ||
fprintf("At 1.8V, Design %d has lowest maximum absolute error of %.4f \n", design, max_abs_error_lst); | ||
[mean_abs_error_lst, design] = min(err_range_array(4, 1, c, :)); | ||
fprintf("At 1.8V, Design %d has lowest mean absolute error of %.4f \n", design, mean_abs_error_lst); | ||
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%[max_abs_error_lst, design] = min(err_range_array(3, 2, c, :)); | ||
%fprintf("At 1.2V, Design %d has lowest maximum absolute error of %.4f \n", design, max_abs_error_lst); | ||
%[mean_abs_error_lst, design] = min(err_range_array(4, 2, c, :)); | ||
%fprintf("At 1.2V, Design %d has lowest mean absolute error of %.4f \n", design, mean_abs_error_lst); |
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clc; clear all; | ||
% This script generates an excel sheet that maps the design number of a | ||
% sensor to its silicon configurations: header type, std cell type, N_hdr | ||
% and N_inv. | ||
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% Initialize Arrays | ||
SensorDesign = zeros(64,1); | ||
HeaderType = strings(64,1); | ||
StdCellType = strings(64,1); | ||
N_hdr = zeros(64,1); | ||
N_inv = zeros(64,1); | ||
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for i = 0:63 | ||
SensorDesign(i+1, 1) = i; | ||
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% Determine Header Type | ||
hdrType = floor(i/32); | ||
if (hdrType == 0) | ||
HeaderType(i+1, 1) = "A"; | ||
else | ||
HeaderType(i+1, 1) = "B"; | ||
end | ||
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% Determine StdCellType | ||
stdCellType = floor(mod(i, 32)/16); | ||
if (stdCellType == 0) | ||
StdCellType(i+1, 1) = "hs"; | ||
else | ||
StdCellType(i+1, 1) = "hd"; | ||
end | ||
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% Determine N_hdr | ||
N_hdr(i+1, 1) = 2*floor(mod(i, 16)/4) + 3; | ||
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% Determine N_inv | ||
N_inv(i+1, 1) = 2*mod(i, 4) + 5; | ||
end | ||
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T = table(SensorDesign, HeaderType, StdCellType, N_hdr, N_inv); | ||
filename = "../SensorToConfigMapping.xlsx"; | ||
writetable(T, filename, 'Sheet', 'Sheet', 'WriteVariableNames', true); |
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function [design, FoM, power, res, EnC] = EvalDesignFoM(drange, min_order, inacc_B_arr, inacc_th, FoM_B_arr, power_B_arr, res_B_arr, EnC_B_arr) | ||
% Find the best design based on FoM | ||
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design = 1; | ||
FoM_min = 1e6; | ||
for i = 1:length(drange) | ||
d = drange(i); | ||
% Only find for those with a reasonable inaccuracy | ||
if (inacc_B_arr(1, d) < inacc_th) | ||
[~, sorted_ind] = sort(FoM_B_arr(1, :, d)); | ||
FoM_Nth_min = FoM_B_arr(1, sorted_ind(min_order), d); | ||
if (FoM_Nth_min < FoM_min) && (FoM_Nth_min > 0) | ||
FoM_min = FoM_Nth_min; | ||
design = d; | ||
end | ||
end | ||
end | ||
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[~, sorted_ind] = sort(FoM_B_arr(1, :, design)); | ||
FoM = FoM_B_arr(1, sorted_ind(min_order), design); | ||
power = power_B_arr(1, sorted_ind(min_order), design); | ||
res = res_B_arr(1, sorted_ind(min_order), design); | ||
EnC = EnC_B_arr(1, sorted_ind(min_order), design); | ||
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end |
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function [params, inacc_arr, params_sec, inacc_arr_sec, Nc_A, indlist_A, inacc_B, indlist_B] = ... | ||
EvalDesignGivenRange(freq_arr, tlist, tstart_ind, twin_len, pcalib, inacc_th, Nc_B, order_sec) | ||
% This function evaluate a single temperature design/instance's inaccuracy | ||
% across multiple chips under a given temperature range. | ||
% It returns fitted parameter pairs for each chip, | ||
% inaccuracies across chips and temperatures, and | ||
% metric A: the number of chips with inaccuracy below a threshold and | ||
% their indices, and | ||
% metric B: the minimal-possible max-inaccuracy given the number of good | ||
% chips we need, also return the their indices. | ||
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% metric A is about the best reliability or least variation | ||
% while metric B is about the best inaccuracy | ||
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% Input: | ||
% freq_arr - Ntemp x Nchip | ||
% tlist - Ntemp x 1 | ||
% tstart_ind - 1x1, index of starting temperature | ||
% twin_len - 1x1, length of temperature range, in 10C-step indices | ||
% pcalib - 1x1, calibration point index w.r.t. tstart_ind, e.g., 2 means | ||
% 20C above tlow and under thigh | ||
% inacc_th - 1x1, threshold of inaccuracy | ||
% Nc_B - 1x1, number of good chips we need | ||
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% Output: | ||
% params - 2 x Nchip | ||
% inacc_arr - Ntemp x Nchip | ||
% Nc_A - 1x1, the number of chips with inaccuracy below a threshold | ||
% indlist_A - 2 x Nchip, the chip indices for metric A | ||
% inacc_B - 1x1, the minimal-possible max-inaccuracy given Nc_B, | ||
% indlist_B - 2 x Nc_B, the chip indices for metric B | ||
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TZiK = 273.15; scale = 1; | ||
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[Ntemp, Nchip] = size(freq_arr); | ||
params = zeros(2, Nchip); | ||
T_array = zeros(Ntemp, Nchip); | ||
inacc_arr = zeros(Ntemp, Nchip); | ||
metric_arr = zeros(3, Nchip); | ||
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% Fit the design for each chip | ||
p1 = tstart_ind + pcalib; | ||
p2 = tstart_ind + twin_len - pcalib; | ||
for c = 1:Nchip | ||
% Fit the curve | ||
flist = freq_arr(:, c); | ||
k = (tlist(p2) - tlist(p1)) / (log(flist(p2)) * (tlist(p2) + TZiK) * scale - log(flist(p1)) * (tlist(p1) + TZiK) * scale); | ||
b = tlist(p1) - k * log(flist(p1)) * (tlist(p1) + TZiK) * scale; | ||
params(1, c) = k; params(2, c) = b; | ||
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% Calculate estimated temperatures and inaccuracies | ||
for t = 1:Ntemp | ||
T_array(t, c) = (scale * TZiK * k * log(flist(t)) + b) / (1 - scale * k * log(flist(t))); | ||
inacc_arr(t, c) = T_array(t, c) - tlist(t); | ||
end | ||
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% Calculate max inaccuracies in the given range | ||
if ( sum(isnan(inacc_arr(tstart_ind:(tstart_ind + twin_len), c))) == 0 ) | ||
metric_arr(1, c) = max(inacc_arr(tstart_ind:(tstart_ind + twin_len), c)); % largest positive error | ||
metric_arr(2, c) = min(inacc_arr(tstart_ind:(tstart_ind + twin_len), c)); % largest negative error | ||
metric_arr(3, c) = max(abs(metric_arr(1,c)), abs(metric_arr(2,c))); % largest absolute error | ||
else | ||
metric_arr(:, c) = [NaN; NaN; NaN]; | ||
end | ||
end | ||
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% Metric A | ||
Nc_A = 0; indlist_A = zeros(2, Nchip); | ||
for c = 1:Nchip | ||
if (metric_arr(3, c) <= inacc_th) | ||
Nc_A = Nc_A + 1; | ||
indlist_A(:, Nc_A) = [c; metric_arr(3,c)]; | ||
end | ||
end | ||
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% Metric B | ||
[sorted_inacc, sorted_ind] = sort(metric_arr(3, :)); | ||
inacc_B = sorted_inacc(Nc_B); | ||
indlist_B = [sorted_ind(1:Nc_B); sorted_inacc(1:Nc_B)]; | ||
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% Systematic Error Correction | ||
if (inacc_B < 20) % Only do SEC when inaccuracy is not too bad | ||
% get the estimated temp of best Nc_B chips | ||
T_est = T_array(tstart_ind:(tstart_ind + twin_len), indlist_B(1, :)); | ||
% define Nth-order polynomial correction: T_sec = pN * T_est^N + ... + p1 * T_est + p0 | ||
% param = [p0, p1, ... pN] | ||
T_left = tlist(tstart_ind:(tstart_ind + twin_len))'; | ||
T_sec = @(param, T) PolyNthOrder(param, T); | ||
T_right = @(param, T) mean(T_sec(param, T), 2); | ||
% Do Optimization | ||
param0 = zeros(1, order_sec + 1); param0(2) = 1; | ||
opts = optimoptions('lsqcurvefit', 'Display','off'); | ||
[params_sec, ~, ~, ~, ~] = lsqcurvefit(T_right, param0, T_est, T_left, [], [], opts); | ||
% Calculate Corrected Temperature estimation and errors | ||
T_array_sec = T_sec(params_sec, T_array); | ||
inacc_arr_sec = T_array_sec - tlist'; | ||
else | ||
params_sec = zeros(1, order_sec+1); params_sec(2) = 1; | ||
inacc_arr_sec = inacc_arr; | ||
end | ||
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end |
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function [design, inacc_sub_arr, inacc_sub_arr_sec, pos_inacc, neg_inacc, sigma, sigma_sec, pos_sigma_inacc, neg_sigma_inacc] = EvalDesignInacc(drange, inacc_arr, inacc_arr_sec, inacc_B_arr, indlist_B_arr, tstart_ind, twin_len) | ||
% Find the best design based on inacc_B given design # range, and evaluate | ||
% its inaccuracies | ||
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[~, design] = min(inacc_B_arr(1, drange)); | ||
design = drange(design); | ||
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inacc_sub_arr = inacc_arr(tstart_ind:(tstart_ind + twin_len), indlist_B_arr(1, :, design), design); | ||
inacc_sub_arr_sec = inacc_arr_sec(tstart_ind:(tstart_ind + twin_len), indlist_B_arr(1, :, design), design); | ||
% Calculate Max/Min Inaccuracy | ||
pos_inacc = max(max(inacc_sub_arr)); | ||
neg_inacc = min(min(inacc_sub_arr)); | ||
pos_inacc_sec = max(max(inacc_sub_arr_sec)); | ||
neg_inacc_sec = min(min(inacc_sub_arr_sec)); | ||
pos_inacc = [pos_inacc; pos_inacc_sec]; | ||
neg_inacc = [neg_inacc; neg_inacc_sec]; | ||
% Calculate 3-sigma Inaccuracy | ||
sigma = [3*std(inacc_sub_arr, 1, 2), -3*std(inacc_sub_arr, 1, 2)] + mean(inacc_sub_arr, 2); | ||
pos_sigma_inacc = max(max(sigma)); | ||
neg_sigma_inacc = min(min(sigma)); | ||
sigma_sec = [3*std(inacc_sub_arr_sec, 1, 2), -3*std(inacc_sub_arr_sec, 1, 2)] + mean(inacc_sub_arr_sec, 2); | ||
pos_sigma_inacc_sec = max(max(sigma_sec)); | ||
neg_sigma_inacc_sec = min(min(sigma_sec)); | ||
pos_sigma_inacc = [pos_sigma_inacc; pos_sigma_inacc_sec]; | ||
neg_sigma_inacc = [neg_sigma_inacc; neg_sigma_inacc_sec]; | ||
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end |
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fprintf("Explore High Temp Range......\n"); | ||
% Explore high-temp range | ||
tstart_ind = 5; % 0C | ||
twin_len = 12; % 0C + 120C = 120C | ||
pcalib = 1; % +/- 10C calibration | ||
% Explore the best designs out of 64 | ||
params_arr = zeros(2, Nchip, 64); | ||
inacc_arr = zeros(Ntemp, Nchip, 64); | ||
params_sec_arr = zeros(order_sec + 1, 64); | ||
inacc_arr_sec = zeros(Ntemp, Nchip, 64); | ||
Nc_A_arr = zeros(1, 64); | ||
indlist_A_arr = zeros(2, Nchip, 64); | ||
inacc_B_arr = zeros(1, 64); | ||
indlist_B_arr = zeros(2, Nc_B, 64); | ||
for design = 1:64 | ||
freq_arr = freq_data_array(:, :, design); | ||
[params, inacc, params_sec, inacc_sec, Nc_A, indlist_A, inacc_B, indlist_B] = ... | ||
EvalDesignGivenRange(freq_arr, tlist, tstart_ind, twin_len, pcalib, inacc_th, Nc_B, order_sec); | ||
params_arr(:, :, design) = params; | ||
inacc_arr(:, :, design) = inacc; | ||
params_sec_arr(:, design) = params_sec; | ||
inacc_arr_sec(:, :, design) = inacc_sec; | ||
Nc_A_arr(:, design) = Nc_A; | ||
indlist_A_arr(:, :, design) = indlist_A; | ||
inacc_B_arr(:, design) = inacc_B; | ||
indlist_B_arr(:, :, design) = indlist_B; | ||
end | ||
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% Best design with header-A | ||
[design, inacc_sub_arr, inacc_sub_arr_sec, pos_inacc, neg_inacc, ~, sigma_sec, pos_sigma_inacc, neg_sigma_inacc] = ... | ||
EvalDesignInacc(1:32, inacc_arr, inacc_arr_sec, inacc_B_arr, indlist_B_arr, tstart_ind, twin_len); | ||
fprintf("Header-A Design %d has lowest maximum absolute error. \n", design); | ||
fprintf("Max/Min error w/o SEC is %f/+%f degreeC. \n", neg_inacc(1), pos_inacc(1)); | ||
fprintf("3-sigma error w/o SEC is %f/+%f degreeC. \n", neg_sigma_inacc(1), pos_sigma_inacc(1)); | ||
fprintf("Max/Min error w/ SEC is %f/+%f degreeC. \n", neg_inacc(2), pos_inacc(2)); | ||
fprintf("3-sigma error w/ SEC is %f/+%f degreeC. \n", neg_sigma_inacc(2), pos_sigma_inacc(2)); | ||
% Plot Inaccuracy and 3-sigma against temp | ||
[fig, hdl] = PlotInacc(fig, tlist(tstart_ind:(tstart_ind + twin_len)), inacc_sub_arr, inacc_sub_arr_sec, sigma_sec, design); | ||
saveas(hdl, './Figures/InaccVStemp_hdrA_hr.emf'); | ||
fprintf("\n"); | ||
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% Best design with header-B | ||
[design, inacc_sub_arr, inacc_sub_arr_sec, pos_inacc, neg_inacc, ~, sigma_sec, pos_sigma_inacc, neg_sigma_inacc] = ... | ||
EvalDesignInacc(33:64, inacc_arr, inacc_arr_sec, inacc_B_arr, indlist_B_arr, tstart_ind, twin_len); | ||
fprintf("Header-B Design %d has lowest maximum absolute error. \n", design); | ||
fprintf("Max/Min error w/o SEC is %f/+%f degreeC. \n", neg_inacc(1), pos_inacc(1)); | ||
fprintf("3-sigma error w/o SEC is %f/+%f degreeC. \n", neg_sigma_inacc(1), pos_sigma_inacc(1)); | ||
fprintf("Max/Min error w/ SEC is %f/+%f degreeC. \n", neg_inacc(2), pos_inacc(2)); | ||
fprintf("3-sigma error w/ SEC is %f/+%f degreeC. \n", neg_sigma_inacc(2), pos_sigma_inacc(2)); | ||
% Plot Inaccuracy and 3-sigma against temp | ||
[fig, hdl] = PlotInacc(fig, tlist(tstart_ind:(tstart_ind + twin_len)), inacc_sub_arr, inacc_sub_arr_sec, sigma_sec, design); | ||
saveas(hdl, './Figures/InaccVStemp_hdrB_hr.emf'); | ||
fprintf("\n"); |
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