Specify Maximum Number of Threads to Run Parallel for-Loops in the Generated Code - MATLAB & Simulink (original) (raw)

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Using MATLAB® Coder™, you can specify the maximum number of threads to run parallelfor-loops in the generated C/C++ code. You can also cross-compile the code, that is, generate the code on the host hardware processor and execute it on the target hardware processor. Depending on the target hardware platform, you can specify the number of threads.

You can set the number of threads in the generated code in different ways. The table lists these options with their precedence order. The precedence determines the order of execution of these options in which the MATLAB Coder sets the number of threads. If the value of these options equals their default value, the precedence order is moved to the next option listed in the table.

If you do not set any of these options, then, by default, the generated parallel code uses the maximum number of threads available on the target hardware during run time. This use of the maximum number of threads is enabled by Open Multiprocessing (OpenMP) pragma omp_get_max_threads in the generated code.

Specify Number of Threads

To specify the maximum number of CPU threads, use one of these approaches:

• In a code configuration object, set theEnableAutoParallelization property totrue and specify a value for theNumberOfCpuThreads property.
• In the Code Generation Settings dialog box, select the Enable automatic parallelization check box and enter a value for the Maximum number of CPU threads parameter.

The maximum number of CPU threads that you configure applies toparfor-loops and automatically parallelizedfor-loops.

For example, consider these MATLAB functions parforExample andautoparExample.

The parforExample function usesparfor-loop with the maximum number of threads set to 6.

function y = parforExample(n) %#codegen y = ones (1,n); parfor (i = 1:n, 6) y(i) = 1; end end

The autoparExample function uses afor-loop. EnableAutomaticParallelization

function y = autoparExample(n) %#codegen y = ones (1,n); for i = 1:n y(i) = 1; end end

Using the MATLAB functions previously specified, this table lists different examples for setting the number of threads in the parallel generated code.

Create Custom Hardware Processor

To add a target processor:

1. Create a copy of an existing target processor.
   processor = target.get('Processor', 'ARM Compatible-ARM Cortex-A');
2. Update the number of cores, number of threads per core, and the name of the new processor.
   processor.NumberOfCores = 4;
   processor.NumberOfThreadsPerCore = 2;
   processor.Name = '4coreprocessor';
3. Add the target.Processor object to an internal database.
4. Select the new processor as the target processor.
   cfg = coder.config('lib');
   cfg.HardwareImplementation.ProdHWDeviceType = 'ARM Compatible->4coreprocessor';

In the MATLAB Coder app, you can choose the custom hardware processor that you have created at command line by using target.get and target.add classes.

Alternatively, you can create a target processor by using target.Processor and target.LanguageImplementation classes. For more information, see Register New Hardware Devices.

See Also

parfor | coder.config | coder.MexCodeConfig | coder.CodeConfig | coder.EmbeddedCodeConfig | target

Topics

• Algorithm Acceleration Using Parallel for-Loops (parfor)
• Specify Maximum Number of Threads in parfor-Loops