Parallelisation Talk Examples – Parallel.ForEach

These are some code examples from my introductory talk on Parallelisation. Showing the difference between a standard sequential foreach loop and its parallel equivalent.

Code example 1: Serial processing of a foreach loop

class Program
{
    private static Random rnd = new Random();

    static void Main(string[] args)
    {
        DateTime start = DateTime.UtcNow;

        IEnumerable items = Enumerable.Range(0,20);

        foreach(int item in items)
            ProcessLoop(item);

        DateTime end = DateTime.UtcNow;
        TimeSpan duration = end - start;

        Console.WriteLine("Finished. Took {0}", duration);

        Console.ReadLine();
    }

    private static void ProcessLoop(int item)
    {
        Console.WriteLine("Processing item {0}", item);

        // Simulate similar but slightly variable length processing
        int pause = rnd.Next(900, 1100);
        Thread.Sleep(pause);
    }
}

The output of the above code may look something like this:

As you can see this takes roughly of 20 seconds to process 20 items with each item taking about one second to process.

Code Example 2: Parallel processing of a foreach loop

The Parallel class can be found in the System.Threading.Tasks namespace.

class Program
{
    private static Random rnd = new Random();

    static void Main(string[] args)
    {
        DateTime start = DateTime.UtcNow;

        IEnumerable items = Enumerable.Range(0,20);

        Parallel.ForEach(items,
            (item) => ProcessLoop(item));

        DateTime end = DateTime.UtcNow;
        TimeSpan duration = end - start;

        Console.WriteLine("Finished. Took {0}", duration);

        Console.ReadLine();
    }

    private static void ProcessLoop(int item)
    {
        Console.WriteLine("Processing item {0}", item);

        // Simulate similar but slightly variable length processing
        int pause = rnd.Next(900, 1100);
        Thread.Sleep(pause);
    }
}

The output of the above code may look something like this:

The result of this code is that it takes roughly 5 second to process the 20 items. I have a 4 core processor so it would be in line with the expectation that the work is distributed across all 4 cores.