Setup

Start by ensuring the Simulation Data Inspector is empty and Parallel Computing Toolbox support is configured to import runs created on local workers automatically. Then, create a vector of filter parameter values to use in each simulation.

% Make sure the Simulation Data Inspector is empty, and PCT support is% enabled.Simulink.sdi.clear Simulink.sdi.enablePCTSupport('local')% Define Ts valuesTs_vals = (0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1];

Initialize Parallel Workers

Use gcp to create a pool of local workers to run parallel simulations if you don't already have one. In anspmdcode block, load theslexAircraftExamplemodel and select signals to log. To avoid data concurrency issues usingsiminparfor, create a temporary directory for each worker to use during simulations.

p = gcp;

Starting parallel pool (parpool) using the 'local' profile ... connected to 4 workers.

spmd% Load system and select signals to logload_system('slexAircraftExample') Simulink.sdi.markSignalForStreaming('slexAircraftExample/Pilot', 1,'on') Simulink.sdi.markSignalForStreaming('slexAircraftExample/Aircraft Dynamics Model', 4,'on')% Create temporary directory on each workerworkDir = pwd; addpath(workDir) tempDir = tempname; mkdir(tempDir) cd(tempDir)end

Run Parallel Simulations

Useparforto run the seven simulations in parallel. Select the value forTsfor each simulation, and modify the value ofTsin the model workspace. Then, run the simulation and build an array ofSimulink.sdi.WorkerRunobjects to access the data with the Simulation Data Inspector. After theparforloop, use anotherspmdsegment to remove the temporary directories from the workers.

parforindex = 1:7% Select value for TsTs_val = Ts_vals(index);% Change the filter time constant and simulatemodelWorkspace = get_param('slexAircraftExample','modelworkspace'); modelWorkspace.assignin('Ts',Ts_val) sim('slexAircraftExample')% Create a worker run for each simulationworkerRun(index) = Simulink.sdi.WorkerRun.getLatestendspmd% Remove temporary directoriescd(workDir) rmdir(tempDir,'s') rmpath(workDir)end

Get Dataset Objects from Parallel Simulation Output

ThegetDatasetmethod puts the data from aWorkerRuninto aDatasetobject so you can easily post-process.

ds(7) = Simulink.SimulationData.Dataset;fora = 1:7 ds(a) = workerRun(a).getDataset;endds(1)

ans = Simulink.SimulationData.Dataset '' with 2 elements Name BlockPath __________ ________________________________________ 1 [1x1 Signal] alpha, rad ...rcraftExample/Aircraft Dynamics Model 2 [1x1 Signal] Stick slexAircraftExample/Pilot - Use braces { } to access, modify, or add elements using index.

Get DatasetRef Objects from Parallel Simulation Output

For big data workflows, use thegetDatasetRefmethod to reference the data associated with theWorkerRun.

forb = 1:7 datasetRef(b) = workerRun(b).getDatasetRef;enddatasetRef(1)

ans = DatasetRef with properties: Name: 'Run 3: slexAircraftExample' Run: [1×1 Simulink.sdi.Run] numElements: 2

Process Parallel Simulation Data in the Simulation Data Inspector

You can also create localRunobjects to analyze and visualize your data using the Simulation Data Inspector API. This example adds a tag indicating the filter time constant value for each run.

forc = 1:7 Runs(c) = workerRun(c).getLocalRun; Ts_val_str = num2str(Ts_vals(c)); desc = strcat('Ts = ', Ts_val_str); Runs(c).Description = desc; Runs(c).Name = strcat('slexAircraftExample run Ts=', Ts_val_str);end

Clean Up Worker Repositories

Clean up the files used by the workers to free up disk space for other simulations you want to run on your worker pool.

Simulink.sdi.cleanupWorkerResources