[c#] Parallel.ForEach vs Task.Factory.StartNew

What is the difference between the below code snippets? Won't both be using threadpool threads?

For instance if I want to call a function for each item in a collection,

Parallel.ForEach<Item>(items, item => DoSomething(item));

vs

foreach(var item in items)
{
  Task.Factory.StartNew(() => DoSomething(item));
}

I did a small experiment of running a method "1,000,000,000 (one billion)" times with "Parallel.For" and one with "Task" objects.

I measured the processor time and found Parallel more efficient. Parallel.For divides your task in to small work items and executes them on all the cores parallely in a optimal way. While creating lot of task objects ( FYI TPL will use thread pooling internally) will move every execution on each task creating more stress in the box which is evident from the experiment below.

I have also created a small video which explains basic TPL and also demonstrated how Parallel.For utilizes your core more efficiently http://www.youtube.com/watch?v=No7QqSc5cl8 as compared to normal tasks and threads.

Experiment 1

Parallel.For(0, 1000000000, x => Method1());

Experiment 2

for (int i = 0; i < 1000000000; i++)
{
    Task o = new Task(Method1);
    o.Start();
}

In my view the most realistic scenario is when tasks have a heavy operation to complete. Shivprasad's approach focuses more on object creation/memory allocation than on computing itself. I made a research calling the following method:

public static double SumRootN(int root)
{
    double result = 0;
    for (int i = 1; i < 10000000; i++)
        {
            result += Math.Exp(Math.Log(i) / root);
        }
        return result; 
}

Execution of this method takes about 0.5sec.

I called it 200 times using Parallel:

Parallel.For(0, 200, (int i) =>
{
    SumRootN(10);
});

Then I called it 200 times using the old-fashioned way:

List<Task> tasks = new List<Task>() ;
for (int i = 0; i < loopCounter; i++)
{
    Task t = new Task(() => SumRootN(10));
    t.Start();
    tasks.Add(t);
}

Task.WaitAll(tasks.ToArray()); 

First case completed in 26656ms, the second in 24478ms. I repeated it many times. Everytime the second approach is marginaly faster.

Parallel.ForEach will optimize(may not even start new threads) and block until the loop is finished, and Task.Factory will explicitly create a new task instance for each item, and return before they are finished (asynchronous tasks). Parallel.Foreach is much more efficient.