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Run Parallel Simulations

The parsim command allows you to run parallel (simultaneous) simulations of your model (design). In this context, parallel runs mean multiple simulations at the same time on different workers. The parsim function makes it easy for you to run the same model with different inputs or different parameter settings in scenarios such as Monte Carlo analyses, parameter sweeps, model testing, experiment design, and model optimization. Running a single simulation in parallel by decomposing the model into smaller components and running those individual pieces simultaneously on multiple workers is currently not supported.

You can run multiple simulations from the Simulink Editor using the Multiple Simulations panel. You can pick a block parameter of interest from the model canvas and specify values that you want to use for the simulations. With the Multiple Simulations panel, you can provide configurations such as Use Parallel to run your simulations in parallel. To run the simulations that you have set up, first, select the design study, then in the Simulink® Toolstrip, on the Simulation tab, click Run All. Once the simulations are complete, you can view and manage the results in Simulation Manager. For more information, see Multiple Simulations Panel: Simulate for Different Values of Stiffness for a Vehicle Dynamics System and Configure and Run Simulations with Multiple Simulations Panel.

To run the simulations in parallel with using the parsim function, you need a Parallel Computing Toolbox™ for local workers. In addition, you can use MATLAB® Parallel Server™ for multiple computer clusters, clouds, and grids. In the absence of Parallel Computing Toolbox and MATLAB Parallel Server, the parsim function runs the simulations in serial. For more information, see Parallel Computing Toolbox and MATLAB Parallel Server.

If no parallel pool exists, the parsim function creates a pool from the default cluster profile . To use a cluster other than the default, create a pool with that cluster profile before calling the parsim function.

This example runs multiple simulations in parallel for a set of sweep parameters.

mdl = "sldemo_suspn_3dof";
openExample(...
    "simulink_features/MultipleSimulationsWorkflowTipsExample",...
    supportingFile=mdl)

Cfsweep  = 2500*(0.05:0.1:0.95);
numSims   = numel(Cfsweep);

simIn(1:numSims) = Simulink.SimulationInput(mdl);
for idx = 1:numSims
    simIn(idx) = setBlockParameter(simIn(idx),...
                         (mdl + "/Road-Suspension Interaction"),...
                          "Cf",num2str(Cfsweep(idx)));
end

simOut = parsim(simIn);

How parsim Works

The parsim function runs simulations with different parameters and values based on the Simulink.SimulationInput object. Each SimulationInput object specifies one simulation of the model. An array of these objects can be created for multiple simulations. For more information, see Running Multiple Simulations.

You can use these functions and properties on the Simulink.SimulationInput object:

  • setVariables - Change variables in base workspace, data dictionary, or model workspace

  • setBlockParameter - Change block parameters

  • setModelParameter - Change model parameters

  • setPreSimFcn - Specify MATLAB functions to run before each simulation for customization and post-processing results on the cluster

  • setPostSimFcn - Specify MATLAB functions to run after each simulation for customization and post-processing results on the cluster

  • InitialState - Change the Initial State

  • ExternalInput - Specify a numerical array, timeseries, or Dataset object as external inputs to the model

This flowchart shows a general sequence of events that occur when the parsim function is executed

Changes to model library blocks can be overwritten when using the parsim function. When models are set up on new workers, model inherits properties directly from the worker library. Use the SetUpFcn name-value argument for the parsim function to transfer the model library block changes to the workers.

See Also

Objects

Functions

Tools

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