Simulink.sdi.WorkerRun.getLatest

R2026b

Create worker run for latest run

Syntax

workerRun = Simulink.sdi.WorkerRun.getLatest

Description

workerRun = Simulink.sdi.WorkerRun.getLatest creates a Simulink.sdi.WorkerRun object for the latest run on a Parallel Computing Toolbox™ worker.

Examples

Access Data from Parallel Simulation

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

Setup

Clear the Simulation Data Inspector and check 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 ThreeSigs 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;
spmd
    load_system("ThreeSigs")
    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("ThreeSigs","modelworkspace");
    assignin(modelWorkspace,"Ts",Ts_val)
    sim("ThreeSigs");
    
    % 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 3 elements

                         Name      BlockPath      
                         ________  ______________ 
    1  [1x1 Signal]      sineSig   ThreeSigs/Out1
    2  [1x1 Signal]      randSig   ThreeSigs/Out2
    3  [1x1 Signal]      chirpSig  ThreeSigs/Out3

  - 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: 3

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("ThreeSignals 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

Version History

Introduced in R2017b