Parallel Programming with Microsoft .Net : Dynamic Task Parallelism - The Basics

The following code shows a binary tree.

public class Tree<T>
{
  public T       Data  { get; set; }
  public Tree<T> Left  { get; set; }
  public Tree<T> Right { get; set; }
}

If you want to perform an action on each data value in the tree, you need to visit each node. This is known as walking the tree, which is a naturally recursive operation. Here’s an example that uses sequential code.

static void SequentialWalk<T>(Tree<T> tree, Action<T> action)
{
  if (tree == null) return;
  action(tree.Data);
  SequentialWalk(tree.Left, action);
  SequentialWalk(tree.Right, action);
}

You can also use parallel tasks to walk the tree.

static void ParallelWalk<T>(Tree<T> tree, Action<T> action)
{
  if (tree == null) return;
  var t1 = Task.Factory.StartNew(
             () => action(tree.Data));
  var t2 = Task.Factory.StartNew(
             () => ParallelWalk(tree.Left, action));
  var t3 = Task.Factory.StartNew(
             () => ParallelWalk(tree.Right, action));
  Task.WaitAll(t1, t2, t3);
}

You don’t need to create a new task to walk the right side of the tree. If you want, you can use the current task; however, using tasks for both the left and right walks makes sure that exceptions that are thrown by either will be observed.

When you use dynamic task parallelism to perform a tree walk, you no longer visit nodes in a fully predictable order.

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Note:

Dynamic task parallelism results in a less predictable order of execution than sequential code.

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