Simulink.sdi.WorkerRun

Access simulation data from parallel workers

Description

The Simulink.sdi.WorkerRun object provides access to run data generated on Parallel Computing Toolbox™ parallel workers. Create a Simulink.sdi.WorkerRun object on the worker. Then, use the WorkerRun object to access data in your local MATLAB^® session.

Creation

Syntax

workerRun = Simulink.sdi.WorkerRun(runID)

Description

workerRun = Simulink.sdi.WorkerRun(runID) creates a Simulink.sdi.WorkerRun object with the run identifier specified by runID. When you want to create a WorkerRun object of the most recent run, use the Simulink.sdi.WorkerRun.getLatest function.

Input Arguments

runID — Run identifier

positive integer

Run identifier, specified as a positive integer.

Use the Simulink.sdi.getAllRunIDs function to get the run IDs for all the runs in the Simulation Data Inspector.

Object Functions

getDataset	Create Simulink.SimulationData.Dataset object of worker run data
getDatasetRef	Create Simulink.sdi.DatasetRef object for worker run
getLocalRun	Create local run from worker run

Examples

Access Data from Parallel Simulation

Execute parallel simulations of the model slexAircraftExample with different input filter time constants and access the data in different ways using the Simulation Data Inspector programmatic interface.

Setup

Check that the Simulation Data Inspector is empty and that 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.

Simulink.sdi.clear
Simulink.sdi.enablePCTSupport("local")

Ts_vals = [0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1]; 

Initialize Parallel Workers

Use the gcp function to create a pool of local workers to run parallel simulations if you don't already have one. In an spmd code block, load the slexAircraftExample model and select signals to log. To avoid data concurrency issues using sim in parfor, create a temporary directory for each worker to use during simulations.

p = gcp;

Starting parallel pool (parpool) using the 'Processes' profile ...
21-Aug-2024 13:35:54: Job Queued. Waiting for parallel pool job with ID 1 to start ...
21-Aug-2024 13:36:55: Job Queued. Waiting for parallel pool job with ID 1 to start ...
21-Aug-2024 13:37:55: Job Running. Waiting for parallel pool workers to connect ...
Connected to parallel pool with 6 workers.

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

Run Parallel Simulations

Use parfor to run the seven simulations in parallel. Select the value for Ts for each simulation, and modify the value of Ts in the model workspace. Then, run the simulation and build an array of Simulink.sdi.WorkerRun objects to access the data with the Simulation Data Inspector. After the parfor loop, use another spmd segment to remove the temporary directories from the workers.

parfor index = 1:7
    % Select value for Ts
    Ts_val = Ts_vals(index);
    
    % Change the filter time constant and simulate
    modelWorkspace = get_param("slexAircraftExample","modelworkspace");
    assignin(modelWorkspace,"Ts",Ts_val)
    sim("slexAircraftExample");
    
    % Create a worker run for each simulation
    workerRun(index) = Simulink.sdi.WorkerRun.getLatest
end

spmd        
    % Remove temporary directories
    cd(workDir)
    rmdir(tempDir, "s")
    rmpath(workDir)
end

Get Dataset Objects from Parallel Simulation Output

The getDataset function puts the data from a WorkerRun object into a Dataset object so you can easily post-process.

ds(7) = Simulink.SimulationData.Dataset;

for a = 1:7
    ds(a) = getDataset(workerRun(a));
end
ds(1)

ans = 
Simulink.SimulationData.Dataset '' with 12 elements

                         Name        BlockPath                                
                         __________  ________________________________________ 
    1  [1x1 State ]      ''          slexAircraftExample/Actuator Model      
    2  [1x1 Signal]      alpha, rad  ...rcraftExample/Aircraft Dynamics Model
    3  [1x1 State ]      ''          ...cs Model/Pitch Channel/Integrate qdot
    4  [1x1 State ]      ''          ...mics Model/Vertical Channel/Integrate
    5  [1x1 State ]      ''          ...ntroller/Alpha-sensor Low-pass Filter
    6  [1x1 State ]      ''          ...ller/Integrator/Continuous/Integrator
    7  [1x1 State ]      ''          ...ple/Controller/Pitch Rate Lead Filter
    8  [1x1 State ]      ''          ...aftExample/Controller/Stick Prefilter
    9  [1x1 State ]      ''          .../Dryden Wind Gust Models/Q-gust model
   10  [1x1 State ]      ''          .../Dryden Wind Gust Models/W-gust model
   11  [1x1 Signal]      Stick       slexAircraftExample/Pilot               
   12  [1x1 Signal]      alpha, rad  slexAircraftExample/alpha, rad          

  - Use braces { } to access, modify, or add elements using index.

Get DatasetRef Objects from Parallel Simulation Output

For big data workflows, use the getDatasetRef function to reference the data associated with the WorkerRun.

for b = 1:7
    datasetRef(b) = getDatasetRef(workerRun(b));
end
datasetRef(1)

ans = 
  DatasetRef with properties:

           Name: 'Run <run_index>: <model_name>'
            Run: [1×1 Simulink.sdi.Run]
    numElements: 12

Process Parallel Simulation Data in the Simulation Data Inspector

You can also create local Simulink.sdi.Run objects to analyze and visualize your data using the Simulation Data Inspector programmatic interface. This example shows a tag indicating the filter time constant value for each run.

for c = 1:7
    Runs(c) = getLocalRun(workerRun(c));
    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

Alternatives

You can also access, view, and analyze simulation data from Parallel Computing Toolbox workers using the Simulation Data Inspector.

Version History

Introduced in R2017b