How to efficiently load a large Matrix into a Matlab Function Block in Simulink

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Folke Friedrich
Folke Friedrich 2022-3-8
回答： Aniket 2024-9-18
Hello everyone,
I want to upload a large matrix A into a (embedded) Matlab Function Block in Simulink ver. 2021b. However, all the methods I have found or came up with seem to be very inefficient, leading to very large simulation times.
The matrix itself does not change over the course of the simulation, ideally I would import it once and reuse it in every time step.
My first Idea was to simply load the matrix in to the workspace and declare it as a Parameter in the Function Block, i.e.
function func = fcn(A,inputs)
%%% Code %%%
end
however, this leads to the same problem that was described in an old question, which went unanswered back then: The compilation of the model takes upwards of 15 minutes, sldiagnostics shows that the step "Stateflow post-compile notify" alone takes about 900 seconds at times.
This post suggests that disbaling data validation and/or debugging for the Matlab Function Block helps, but I was unable to find how this works in the current version.
My second approach was to load the data inside the Block, like this:
function func = fcn(inputs)
coder.extrinsic('load');
S = load('A.mat') % because simulink warned me to do it like this
A1 = S.A;
end
however, this does not work because of the error
Attempt to extract field 'A' from 'mxArray'.
which I was able to solve by instead using
function func = fcn(inputs)
coder.extrinsic('load');
coder.extrinsic('getfield');
S = load('A.mat') % because simulink warned me to do it like this
A = zeros(N); % preinitialize, N being the size of A
A1 = getfield(S,'A');
end
Which compiles quickly, but the simulation itself takes a very long time, I assume because the data is imported in every timestep.
Does anybody have an idea how to do this more efficiently?
Best regards
Folke

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Aniket
Aniket 2024-9-18
Hi @Folke Friedrich,
I understand that you want to know a way to efficiently load a large matrix into MATLAB ‘Function Block’ in Simulink. In order to do so, consider the following approaches:
1. Model Reference for Compilation Efficiency:
- If the Embedded MATLAB ‘Function Block’ does not change between simulation runs, place it inside a Model Reference. This can significantly reduce compilation time because referenced models are only recompiled when a change is detected. This approach can help mitigate long compilation times.
- For more information, refer to the MathWorks documentation on ‘Model References’:
https://www.mathworks.com/help/simulink/model-reference.html
2. Loading Data Efficiently:
- Pre-load the Matrix in the Workspace: Load the matrix into the MATLAB base workspace before starting the simulation. Use a ‘persistent’ variable to store the matrix within the MATLAB Function Block, ensuring it is only loaded once. Here's an example:
function y = fcn(u)
coder.extrinsic('evalin');
persistent A;
if isempty(A)
A = evalin('base', 'A'); % Load matrix from workspace
end
% Use matrix A in computations
y = A * u;
end
- Using `coder.extrinsic`: If loading the matrix within the block is necessary, use `coder.extrinsic` with a ‘persistent’ variable to ensure the matrix is loaded only once:
function y = fcn(u)
coder.extrinsic('load');
persistent A;
if isempty(A)
S = load('A.mat');
A = S.A;
end
% Use matrix A in computations
y = A * u;
end
3. Disable Data Validity Checking:
Slow simulation speed might be due to data validity checking, which is enabled by default. Disabling this can improve performance. For more information, visit: https://www.mathworks.com/help/simulink/gui/parameterwriterblockvalidation.html
4. Avoid Unnecessary Data Copies:
To further optimize code and reduce computation time, avoid unnecessary copies of data. MATLAB's handling of variable references can be optimized by understanding how data is copied. For detailed guidance, see:
https://www.mathworks.com/help/matlab/matlab_prog/avoid-unnecessary-copies-of-data.html
Implementing these strategies should efficiently manage the large matrix in the Simulink model, reducing both compilation and simulation times.
Hope it helps!

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