I'm looking for a simple implementation of a parallelized (multi-threaded) sort algorithm in C# that can operate on List<T> or Arrays, and possibly using Parallel Extensions but that part isn't strictly necessary.
Edit: Frank Krueger provides a good answer, however I wish to convert that example to one that doesn't use LINQ. Also note that Parallel.Do() seems to have been superceded by Parallel.Invoke().
Thanks.
From "The Darkside" in his article Parallel Extensions to the .Net Framework we have this parallel extensions version of quicksort:
(Edit: Since the link is now dead, interested readers may find an archive of it at the Wayback Machine)
private void QuicksortSequential<T>(T[] arr, int left, int right)
where T : IComparable<T>
{
if (right > left)
{
int pivot = Partition(arr, left, right);
QuicksortSequential(arr, left, pivot - 1);
QuicksortSequential(arr, pivot + 1, right);
}
}
private void QuicksortParallelOptimised<T>(T[] arr, int left, int right)
where T : IComparable<T>
{
const int SEQUENTIAL_THRESHOLD = 2048;
if (right > left)
{
if (right - left < SEQUENTIAL_THRESHOLD)
{
QuicksortSequential(arr, left, right);
}
else
{
int pivot = Partition(arr, left, right);
Parallel.Do(
() => QuicksortParallelOptimised(arr, left, pivot - 1),
() => QuicksortParallelOptimised(arr, pivot + 1, right));
}
}
}
Notice that he reverts to a sequential sort once the number of items is less than 2048.
Parallel.Do is now as Parallel.Invoke, and given big enough arrays, you can expect to gain massive gains(50%!). –
Galvanic Update I now achieve better than 1.7x speedup on a dual core machine.
I thought I would try writing a parallel sorter that worked in .NET 2.0 (I think, check me on this) and that doesn't use anything other than the ThreadPool.
Here are the results of sorting a 2,000,000 element array:
Time Parallel Time Sequential ------------- --------------- 2854 ms 5052 ms 2846 ms 4947 ms 2794 ms 4940 ms ... ... 2815 ms 4894 ms 2981 ms 4991 ms 2832 ms 5053 ms Avg: 2818 ms Avg: 4969 ms Std: 66 ms Std: 65 ms Spd: 1.76x
I got a 1.76x speedup - pretty close to the optimal 2x I was hoping for - in this environment:
Model objectsDateTime properties.This time I used Ben Watson's QuickSort in C#. I changed his QuickSort inner loop from:
QuickSortSequential:
QuickSortSequential (beg, l - 1);
QuickSortSequential (l + 1, end);
to:
QuickSortParallel:
ManualResetEvent fin2 = new ManualResetEvent (false);
ThreadPool.QueueUserWorkItem (delegate {
QuickSortParallel (l + 1, end);
fin2.Set ();
});
QuickSortParallel (beg, l - 1);
fin2.WaitOne (1000000);
fin2.Close ();
(Actually, in the code I do a little load balancing that does seem to help.)
I've found that running this parallel version only pays off when there are more than 25,000 items in an array (though, a minimum of 50,000 seems to let my processor breath more).
I've made as many improvements as I can think of on my little dual core machine. I would love to try some ideas on 8-way monster. Also, this work was done on a little 13" MacBook running Mono. I'm curious how others fare on a normal .NET 2.0 install.
The source code in all its ugly glory is availble here: http://www.praeclarum.org/so/psort.cs.txt. I can clean it up if there's any interest.
For the record here is a version without lamda expressions that will compile in C#2 and .Net 2 + Parallel Extensions. This should also work with Mono with its own implementation of Parallel Extensions (from Google Summer of code 2008):
/// <summary>
/// Parallel quicksort algorithm.
/// </summary>
public class ParallelSort
{
#region Public Static Methods
/// <summary>
/// Sequential quicksort.
/// </summary>
/// <typeparam name="T"></typeparam>
/// <param name="arr"></param>
public static void QuicksortSequential<T>(T [] arr) where T : IComparable<T>
{
QuicksortSequential(arr, 0, arr.Length - 1);
}
/// <summary>
/// Parallel quicksort
/// </summary>
/// <typeparam name="T"></typeparam>
/// <param name="arr"></param>
public static void QuicksortParallel<T>(T[] arr) where T : IComparable<T>
{
QuicksortParallel(arr, 0, arr.Length - 1);
}
#endregion
#region Private Static Methods
private static void QuicksortSequential<T>(T[] arr, int left, int right)
where T : IComparable<T>
{
if (right > left)
{
int pivot = Partition(arr, left, right);
QuicksortSequential(arr, left, pivot - 1);
QuicksortSequential(arr, pivot + 1, right);
}
}
private static void QuicksortParallel<T>(T[] arr, int left, int right)
where T : IComparable<T>
{
const int SEQUENTIAL_THRESHOLD = 2048;
if (right > left)
{
if (right - left < SEQUENTIAL_THRESHOLD)
{
QuicksortSequential(arr, left, right);
}
else
{
int pivot = Partition(arr, left, right);
Parallel.Invoke(new Action[] { delegate {QuicksortParallel(arr, left, pivot - 1);},
delegate {QuicksortParallel(arr, pivot + 1, right);}
});
}
}
}
private static void Swap<T>(T[] arr, int i, int j)
{
T tmp = arr[i];
arr[i] = arr[j];
arr[j] = tmp;
}
private static int Partition<T>(T[] arr, int low, int high)
where T : IComparable<T>
{
// Simple partitioning implementation
int pivotPos = (high + low) / 2;
T pivot = arr[pivotPos];
Swap(arr, low, pivotPos);
int left = low;
for (int i = low + 1; i <= high; i++)
{
if (arr[i].CompareTo(pivot) < 0)
{
left++;
Swap(arr, i, left);
}
}
Swap(arr, low, left);
return left;
}
#endregion
}
int[] arr = new int[1024*1024*128]; ParallelSort.QuicksortParallel(arr); and then partition will be [1,2,3,... array.Length]. It seems to be not valid. –
Conrado A merge sort based on the size of the processor cache, with the blocks being divided between the processors comes to mind.
The merge stage could be done by splitting the merge into n bits with each processor starting to merge the blocks from the correct offset into the blocks.
I have not tried writing this.
(As the relative speed of CPU cache and main ram, is not that far off the relative speed of RAM and Tape as the time the merge sort was discovered, maybe we should start using merge sorts again)
Divide the list you need sorted into equal sized sublists, depending on how many processors you have, and then whenever two parts are done, merge them together to a new part, until there is only one left and all threads completed. Very simple you should be able to implement it yourself, and sorting the lists within each thread can be done using any existing sort algorithm (like in the library).
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