MATLAB: Is it possible to use PARFOR in a compiled application on the parallel configuration

MATLAB Compilermdcsparallelparfor

I would like to know if it is possible to compile an application that uses PARFOR and is to be run on parallel configurations other than local.

Best Answer

Applications using PARFOR can be compiled to run on parallel configurations other than local. Parallel configuration information can be stored in a MAT file. This MAT file can be included with the executable at compile time, or provided with the option -MCRUSERDATA at runtime (see detailed information further below).

You can find instructions on how to export a MAT file containing the parallel configuration information at the following link:

Compile and Deploy a Standalone Application with the Parallel Computing Toolbox

http://www.mathworks.com/help/compiler/use-the-parallel-computing-toolbox.html

In order to be able to run the standalone on a target machine and have it use the cluster, the MATLAB Distributed Computing Server (MDCS) is required.

Once the executable and the MAT file have been given to the end user, the user can make use of the cluster by calling the executable with the -MCRUSERDATA flag as in the following code:

parallelapp.exe -mcruserdata ParallelConfigurationFile:config.mat

The documentation for what needs to occur on the user's end is discussed at the following link:

https://www.mathworks.com/help/compiler/deployment-process.html

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MATLAB: Can MATLAB Distributed Computing Server (MDCS) be used to compile an application with the MATLAB Compiler

Due to the complexity of MATLAB Compiler's interaction with external system compilers, distributed compilation is not possible.

It is possible to compile an application that will then use the MDCS nodes, but the compilation of the application must be done on a single machine with a traditional license that includes the MATLAB Compiler.

In addition to being unable to compile through a distributed cluster of nodes, MATLAB Compiler has some limitations on which toolboxes and functions are supported. A full list of supported compiler toolboxes and limitations can be found on the following pages:

MATLAB Compiler - Support for MATLAB and Toolboxes

https://www.mathworks.com/products/compiler/compiler_support.html

MATLAB Compiler - Limitations

https://www.mathworks.com/help/compiler/limitations-about-what-may-be-compiled.html

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:

 myExe.exe -mcruserdata ParallelConfigurationFile:myConfig.mat

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:

 matlabpool % Open a matlabpool using the default configuration
 ... %do stuff
 matlabpool close

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: Can MATLAB Distributed Computing Server (MDCS) be used to compile an application with the MATLAB Compiler

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

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