matlab-codegen-deploy

MATLAB Codegen Deploy

Use this skill when MATLAB or Simulink algorithms need to become generated code or deployable artifacts.

Workflow

1. Identify target: MEX, C/C++, embedded C, CUDA, HDL, PLC, or packaged app.
2. Verify required products with ver and license.
3. Isolate the algorithm into a codegen-friendly function.
4. Define input types with coder.typeof or representative test vectors.
5. Generate the smallest artifact first, usually MEX.
6. Compare generated result against MATLAB golden output.
7. Save generated code, logs, reports, and validation metrics.

Self-Compile and Verify Preference

The user expects generated MATLAB/Simulink work to compile and verify itself after writing. Do not stop at source generation when a build or smoke check is feasible:

1. For MATLAB Coder, run codegen and then compare generated/MEX output against MATLAB golden output when compiler support exists.
2. For Simulink Coder, update/compile the model first, run simulation, then call slbuild only after simulation passes.
3. For embedded targets such as STM32, first try the configured hardware target and toolchain; if it fails, capture the exact missing package/compiler message and generate the closest portable C fallback if possible.
4. Verify generated .c, .h, project, library, elf/axf/hex/bin, or fallback artifacts exist and are nonempty.
5. Report clearly which stage passed: model update, simulation, code generation, toolchain build, binary generation, or only portable fallback.

MATLAB Coder Pattern

Use this pattern before larger deployment:

cfg = coder.config("mex");
codegen -config cfg myFunction -args {coder.typeof(0,[100 1],[1 0])}
gold = myFunction(x);
actual = myFunction_mex(x);
assert(norm(gold-actual) < 1e-9)

Embedded Readiness

Check:

• Fixed-size vs variable-size arrays.
• Dynamic allocation and recursion.
• Unsupported functions.
• Numeric overflow and fixed-point scaling.
• Stack and heap impact.
• Timing budget and hardware target assumptions.