Question

Amazingly, using PLINQ did not yield benefits on a small test case I created; in fact, it was even worse than usual LINQ.

Here’s the test code:

    int repeatedCount = 10000000;
    private void button1_Click(object sender, EventArgs e)
    {
        var currTime = DateTime.Now;
        var strList = Enumerable.Repeat(10, repeatedCount);
        var result = strList.AsParallel().Sum();

        var currTime2 = DateTime.Now;
        textBox1.Text = (currTime2.Ticks-currTime.Ticks).ToString();

    }

    private void button2_Click(object sender, EventArgs e)
    {
        var currTime = DateTime.Now;
        var strList = Enumerable.Repeat(10, repeatedCount);
        var result = strList.Sum();

        var currTime2 = DateTime.Now;
        textBox2.Text = (currTime2.Ticks - currTime.Ticks).ToString();
    }

The result?

textbox1: 3437500
textbox2: 781250

So, LINQ is taking less time than PLINQ to complete a similar operation!

What am I doing wrong? Or is there a twist that I don’t know about?

Edit: I’ve updated my code to use stopwatch, and yet, the same behavior persisted. To discount the effect of JIT, I actually tried a few times with clicking both button1 and button2 and in no particular order. Although the time I got might be different, but the qualitative behavior remained: PLINQ was indeed slower in this case.

Answer 1

First: Stop using DateTime to measure run time. Use a Stopwatch instead. The test code would look like:

var watch = new Stopwatch();

var strList = Enumerable.Repeat(10, 10000000);

watch.Start();
var result = strList.Sum();
watch.Stop();

Console.WriteLine("Linear: {0}", watch.ElapsedMilliseconds);

watch.Reset();

watch.Start();
var parallelResult = strList.AsParallel().Sum();
watch.Stop();

Console.WriteLine("Parallel: {0}", watch.ElapsedMilliseconds);

Console.ReadKey();

Second: Running things in Parallel adds overhead. In this case, PLINQ has to figure out the best way to divide your collection so that it can Sum the elements safely in parallel. After that, you need to join the results from the various threads created and Sum those as well. This isn’t a trivial task.

Using the code above I can see that using Sum() nets a ~95ms call. Calling .AsParallel().Sum() nets around ~185ms.

Doing a task in Parallel is only a good idea if you gain something by doing it. In this case, Sum is a simple enough task that you don’t gain by using PLINQ.