MATLAB: Syms function undefined on parallel pool workers when compiling standalone application

MATLAB CompilerParallel Computing ToolboxsimulationsymbolicSymbolic Math Toolbox

I am trying to run a simulation where I am symbolically generating a set of functions to test during each iteration. I am running several simulations at a time with parfor and it works great on my machine. I am now trying to compile this code to a standalone application to run on AWS since I need more compute power. However when I test the code on my local machine after it compiles I get this error:

'An UndefinedFunction error was thrown on the workers for 'syms'. This might be because the file containing 'syms' is not accessible on the workers. Use addAttachedFiles(pool, files) to specify the required files to be attached. See the documentation for 'parallel.Pool/addAttachedFiles' for more details.'

I don't think I should need to add the symbolic toolbox to the parallel pool… Does anybody know what might be causing this error and how to fix it? Thanks!

Best Answer

Nothing from the symbolic toolbox can be compiled.

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Hope it helps :)

MATLAB: How to define ‘local’ matlabpool size at runtime for Parallel Computing Toolbox use in compiled MATLAB code

Hi Nick,

When you compile a PCT application, all of your configurations get bundled into the compiled application, so if your local configuration has a hard-coded ClusterSize value of 8, then when the compiled application runs, it will always use a ClusterSize of 8, regardless of the number of actual cores on the machine.

You can supply a custom configuration to use for the application using the mcruserdata flag. e.g, if your application is myExe.exe, and your exported configuration is myConfig.mat, then you would use this command:

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See the documentation for more details.

In order to take advantage of this, your code need to be configuration agnostic and always use the default configuration. Your code would then look like this:

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In general, it is better for your compiled code to use the default configuration rather than a hard-coded one because it allows users of the compiled application to run it on different clusters without you having to modify the actual code.

Elwin

Best Answer

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MATLAB: How to change NumWorkers property in compiled applications

MATLAB: How to define ‘local’ matlabpool size at runtime for Parallel Computing Toolbox use in compiled MATLAB code

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