Parallel ForEach vs Task Factory StartNew

Question

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 lt Item gt  items  item   gt  DoSomething item     vs  foreach var item in items      Task Factory StartNew      gt  DoSomething item

User · Answer

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.

User · Answer

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   gt  Method1       Experiment 2  for  int i   0  i  lt  1000000000  i          Task o   new Task Method1       o Start

User · Answer

The first is a much better option   Parallel ForEach  internally  uses a Partitioner lt T gt  to distribute your collection into work items   It will not do one task per item  but rather batch this to lower the overhead involved   The second option will schedule a single Task per item in your collection   While the results will be  nearly  the same  this will introduce far more overhead than necessary  especially for large collections  and cause the overall runtimes to be slower   FYI - The Partitioner used can be controlled by using the appropriate overloads to Parallel ForEach  if so desired   For details  see Custom Partitioners on MSDN   The main difference  at runtime  is the second will act asynchronous   This can be duplicated using Parallel ForEach by doing   Task Factory StartNew       gt  Parallel ForEach lt Item gt  items  item   gt  DoSomething item       By doing this  you still take advantage of the partitioners  but don t block until the operation is complete

User · Answer

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

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

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