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I have built an standalone Matlab application. I was expecting it to be faster than running the application from the Matlab environent but it is indeed a bit slower (1.3 seg per iteration vs 1.5 seg per iteration) I am not counting the init time required by MCR but the execution of my code. Is that the expected performance or should I be obtaining a performance improvement? I haven't found any settings on the deployment tool that could help to reduce execution time.

Thanks in advance

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    Despite lots for buzzwords there is little to be found about this building process. I have the impression it basically creates pcode encrypted files with some wrapper to execute them. So I'd say it is expected. Almost everybody seems to transfer their into a "proper" language after development for speed. Commented Jun 10, 2013 at 10:08

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Applications built with MATLAB Compiler should execute at pretty much exactly the same speed as within MATLAB.

MATLAB Compiler does not convert your MATLAB code into machine code in the same way as a C compiler does for C. What it does is to archive and encrypt your MATLAB code (note, it properly encrypts it, not just pcodes it as a comment suggests), create a thin executable wrapper and package them together, possibly also with MATLAB Compiler Runtime (MCR). MCR is very similar to MATLAB itself, without a graphical user interface, and is freely redistibutable.

When you run the executable, it dearchives and decrypts your MATLAB code and runs it against the MCR. It should run exactly the same, both in terms of results and speed.

Very old versions of MATLAB Compiler (pre-version 4.0) worked in a different way, converting a subset of the MATLAB language into C code, and compiling this. This provided a potentially significant speed-up, but only a subset of the language was supported and results, unless you were careful, could sometimes be different. Similar functionality is now available in the separate MATLAB Coder product.

There are a few small things you can do to improve performance: for example, within deploytool you can specify which toolboxes your application uses. deploytool uses a dependency checker to package up all MATLAB functionality that it thinks your code might possibly depend on, but it can't always tell exactly, as the functions your code needs might change at runtime. It therefore errs on the side of caution and includes more than necessary. By specifying only the toolboxes you know to be necessary, you can speed things up a little (it also speeds up the build process quite a bit).

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Thanks for your comprehensive answer.

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