Waitgroups in Modelica

In Modelica, we don’t have direct equivalents for goroutines or WaitGroups. However, we can simulate similar behavior using the parallelism package and the parfor construct. Here’s how we can create a similar example:

model WaitGroups
  import Modelica.Utilities.Streams.*;
  import Modelica.Utilities.System;

  function worker
    input Integer id;
  algorithm
    print("Worker " + String(id) + " starting\n");
    System.sleep(1000); // Sleep for 1 second to simulate an expensive task
    print("Worker " + String(id) + " done\n");
  end worker;

equation
  algorithm
    parfor i in 1:5 loop
      worker(i);
    end parfor;
end WaitGroups;

This model simulates the behavior of multiple workers running concurrently:

1. We define a worker function that takes an id as input. This function prints a starting message, sleeps for 1 second to simulate work, and then prints a completion message.

2. In the main algorithm section, we use a parfor loop to launch multiple instances of the worker function concurrently. The parfor construct in Modelica allows for parallel execution of the loop iterations.

3. The parfor loop automatically handles the synchronization, similar to how the WaitGroup in the original example waited for all goroutines to complete.

To run this model:

1. Save it in a file named WaitGroups.mo.
2. Use a Modelica simulation environment like OpenModelica or Dymola to compile and run the model.

The output will be similar to:

Worker 1 starting
Worker 2 starting
Worker 3 starting
Worker 4 starting
Worker 5 starting
Worker 1 done
Worker 2 done
Worker 3 done
Worker 4 done
Worker 5 done

Note that the order of workers starting and finishing may vary between runs due to the parallel nature of execution.

It’s important to note that Modelica’s approach to parallelism is different from many other programming languages. It’s designed for equation-based modeling and simulation, so the parallelism is handled at a higher level by the simulation environment. This means that error handling and more complex synchronization patterns might need to be handled differently compared to languages with more low-level concurrency primitives.

For more advanced use cases involving parallel computation in Modelica, you might need to explore additional libraries or tools specific to your simulation environment.