Concurrency vs. Parallelism: A breakfast example

One of the harder problems in Computer Science is concurrency. This summer at my employer, I gave a presentation on asynchrony, which I consider nearly the same thing as concurrency. One of the things that I felt was lacking was my explanation of concurrency vs. parallelism. I ended up just giving a textbook explanation:

• Parallel processing is taking advantage of a lot of processors (local or remote) to run calculations on large volumes of data
• Asynchronous execution is freeing up the processor to do other things while a lengthy operation is occurring

This morning, however, I was making myself breakfast, and I thought up a useful analogy.

A breakfast example

My breakfast this morning consisted of a coffee and two slices of toast with peanut butter.

A perfect example of concurrency was how I made the breakfast: I first started the toast, then put the coffee cup in the Keurig and pushed the brew button on the Keurig. This is a concurrent operation - one job (toasting the bread) was started, and after that began, I (the processor) was freed up to start another job, the "brew coffee" operation.

We can take this analogy further: the toaster can actually process two pieces of bread at once, which is a parallel operation. From here, we can easily see that parallelism is a subset of concurrency: technically, the toaster is technically performing two operations concurrently, what makes it a parallel operation is the fact that it's the same process occurring twice, started at the same time within the same machine.

Should we write this as C#?

public static class Program {
  public static void Main() {
    MakeBreakfast().Wait();
  }

  public static async Task MakeBreakfast() {
    // Start toast - this operation takes the longest to complete, so let's get
    // it started as soon as possible
    var toaster = new StandardToaster(new ElectricitySupplier());
    var toastingTask = toaster.Toast(new WheatBread(), new WheatBread());

    // Now start the Keurig, a relatively short operation
    var brewer = new Keurig(new Water());
    var brewingTask = brewer.Brew(new DarkCoffee());

    // Don't return control to the human until operations complete
    await Task.WhenAll(toastingTask, brewingTask);
  }

  public interface Toaster {
    public Task<IEnumerable<Toast>> Toast(Bread bread, Bread bread);
  }

  public interface Brewer {
    public Task<Coffee> Brew(GroundCoffee groundCoffee);
  }
}

Concurrency and Parallelism in Real Life

The thing about concurrency and parallelism is that you can do this all the time; for example, humans are terrible at multi-tasking (parallel processing), but are great at starting multiple jobs, and then taking action when they finish (concurrent processing).

I encourage everyone to always think of how the things they do in real life apply to different concepts in software development. Since software development is all about automating real life processes, these analogies actually occur much more frequently than one would expect!