Speed Up Frequency Response Estimation Using Parallel
Computing
This example illustrates how to speed up frequency response estimation of Simulink®
models using parallel computing. In some scenarios, the frestimate function estimates
the frequency response of a Simulink model by performing multiple Simulink simulations.
You can distribute these simulations to a pool of MATLAB workers by using Parallel
Computing Toolbox™.
This example requires Parallel Computing Toolbox. You can optionally run simulations on
a computer cluster using MATLAB® Parallel Server™. This example uses the local worker
functionality available in Parallel Computing Toolbox.
Speed up Simulink Simulations Performed by frestimate
When you compute a frequency response using the frestimate function, the majority of
computation time is usually spent in Simulink simulations. To reduce the total simulation
time, you can:
(^1) Use rapid accelerator mode. Use this method when frestimate performs only one
Simulink simulation. For an example, see “Linearization Validation in Frequency
Domain Using FRESTIMATE” on page 5-96.
(^2) Distribute simulations across workers in a MATLAB pool. Use this method when
frestimate performs multiple Simulink simulations. frestimate performs more
than one Simulink simulation when you specify the following:
- A sinestream input signal with the SimulationOrder parameter set to
'OneAtATime'. In this case, each frequency in the sinestream signal is simulated
separately. - Linear analysis points with more than one input point or a nonscalar input point. In
this case, each linearization input point or each channel in a nonscalar linearization
input point yields a separate Simulink simulation.
Using the frestimate function with parallel computing also supports normal,
accelerator, and rapid accelerator modes.
Configure a MATLAB Pool
To use parallel computing to speed up frequency response estimation, configure and start
a pool of MATLAB workers before you run the frestimate function.
5 Frequency Response Estimation