Hi Alessandro,
The Parallel Computing Toolbox in MATLAB supports both Performance (P) and Efficiency (E) cores. P cores offer high computational power and are ideal for compute-bound tasks, while E cores are optimized for power efficiency and better suited for lighter workloads. Starting with R2024a, the 'Processes' profile defaults to using a number of workers equal to the number of P cores on the machine, ensuring optimal performance for intensive computations.
You can adjust the number of workers either through the MATLAB GUI or programmatically:
In the GUI, navigate to Parallel Computing > Create and Manage Clusters, then select the 'Processes'profile in the Cluster Profile Manager and edit the NumWorkers setting.
Programmatically, use:
c = parcluster('Processes')
c.NumWorkers = 10;
saveProfile(c)
Note: For non-compute-bound tasks such as disk I/O or memory-intensive operations, increasing the number of workers beyond the default may improve performance. However, if you're also modifying the number of threads, ensure that the product of workers and threads does not exceed the number of physical cores. Always increase the number of workers gradually and monitor performance, memory usage, and system stability to avoid degradation or crashes. Make sure your system has sufficient memory to support the configured number of MATLAB workers and the workload being executed.
For more details you may also refer to:
