HDLCoder RAM mapping not working

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Amogh
Amogh 2025-4-1
回答： Ryan Baird 2025-4-1
I am trying to convert a matlab code into verilog using HDLCoder
The code im using is as follows
function x = pred3(input)
% Ensure input is single precision
input = single(input);
% Load LUT for sigmoid approximation
persistent x_values sigmoid_values;
if isempty(x_values)
data = coder.load('sigmoid_LUT.mat');
x_values = single(data.x_values);
sigmoid_values = single(data.sigmoid_values);
end
coder.hdl.ramconfig({x_values,sigmoid_values},RAMType="Dual Port")
persistent scaler_mean scaler_std_rec layer1_weight layer1_bias layer2_weight layer2_bias layer3_weight layer3_bias;
if isempty(scaler_mean)
% Load model parameters once
model = coder.load("weights_biases2.mat");
scaler_mean = single(model.scaler_mean);
scaler_std_rec = single(model.std_scaler_rec);
layer1_weight = single(model.layer1_weight);
layer1_bias = single(model.layer1_bias);
layer2_weight = single(model.layer2_weight);
layer2_bias = single(model.layer2_bias);
layer3_weight = single(model.layer3_weight);
layer3_bias = single(model.layer3_bias);
end
coder.hdl.ramconfig({scaler_std_rec,scaler_mean,layer1_weight,layer1_bias,layer2_weight,layer2_bias,layer3_weight,layer3_bias},RAMType="Dual Port")
% Normalize input
input = (input - scaler_mean) .* scaler_std_rec;
% Layer 1: Fully Connected + ReLU
layer1_op = input * layer1_weight' + layer1_bias;
% Replace max(layer1_op, 0) with explicit conditional update
for i = 1:numel(layer1_op)
if layer1_op(i) < 0
layer1_op(i) = 0;
end
end
% Layer 2: Fully Connected + ReLU
layer2_op = layer1_op * layer2_weight' + layer2_bias;
for i = 1:numel(layer2_op)
if layer2_op(i) < 0
layer2_op(i) = 0;
end
end
% Layer 3: Fully Connected (No Activation)
layer3_op = layer2_op * layer3_weight' + layer3_bias;
% Ensure layer3_op is within LUT range without using max/min
x_clipped = layer3_op;
x_max = x_values(1);
x_min = x_values(1);
% Find min and max of x_values manually
for i = 2:length(x_values)
if x_values(i) > x_max
x_max = x_values(i);
end
if x_values(i) < x_min
x_min = x_values(i);
end
end
% Clip layer3_op without using max/min
if x_clipped > x_max
x_clipped = x_max;
elseif x_clipped < x_min
x_clipped = x_min;
end
% Find closest index in LUT
min_diff = abs(x_values(1) - x_clipped);
idx = 1;
for i = 2:length(x_values)
diff = abs(x_values(i) - x_clipped);
if diff < min_diff
min_diff = diff;
idx = i;
end
end
% Lookup sigmoid output
output = sigmoid_values(idx);
% Final decision based on threshold
if output < 0.5
x = single(0);
else
x = single(1);
end
end
However after I run the HDLCoder and after turning on the map persistant varibales to ram the RAM usage in resource report is 0

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回答（1 个）

Ryan Baird
Ryan Baird 2025-4-1
When RAM Mapping fails there should be a warning in the generated report that gives more information about what happened.
In this case, one thing I can see looking at the provided code is that there are non-scalar accesses to the variables intended to be mapped to RAM. I'd expect to see the warning 'RAM mapping failed for variable, "scaler_std_rec", because it has a non-scalar sub-matrix access.' and similar warnings for other variables.
This is related to the current limitation of the RAM Mapping "Each read or write access is for a single element only." The limitations are listed on the page Map Persistent Arrays and dsp.Delay Objects to RAM. The operation "(input - scaler_mean) .* scaler_std_rec" is considered a read to every element of scaler_std_rec in regards to this limitation.
A workaround would be to write this operation and other similar operations as a loops and use coder.unroll to unroll the loops.

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