I made a small program which sorts a Vector of 100000 ints.
I use a quicksort , not the recursive one.
With the single thread version I takes about 22s to complete.
-now the problem and the question:
I have written a second version which
1. first make a partitioning
2. start an independent thread on eatch subpartition = 2Threads
So the sorting continues on 2 separate threads with no locks or anythig to block;
I got almost the same time when running.
Why happens to run in same interval of time.
Will Windows7 be very smart to optimize the code to run on multiple cores even if it is a single thread?
I have a x6 Cpu.
here is the sample code (test code)
constint sizeV = 100000;
//Stack<int> numbers = new Stack<int>();
void push2(Stack<int> s, int a, int b)
int value= sizeV;
for (int i = 0; i < sizeV; ++i)
V[i] = value--;
void exchange(refint x, refint y)
int temp= x;
int partition(int A, int l, int r)
int i = l - 1;
int j = r;
int v= A[r];
while (v < A[--j]) if (j == l) break;
if (i >= j) break;
exchange(ref A[i], ref A[j]);
exchange(ref A[i], ref A[r]);
public ThData(int a, int i, int j)
A = a; l = i; r = j;
void thWorkerParititoner(object data)
int A = ((ThData)data).A;
int l = ((ThData)data).l;
int r = ((ThData)data).r;
quicksort(A, l, r);
void StartQuicksort(int A, int l, int r)
if (r <= l) return;
int i = partition(A, l, r);
Thread t1 = new Thread(thWorkerParititoner);
t1.Start(new ThData (A, l, i-1));
Thread t2 = new Thread(thWorkerParititoner);
t2.Start(new ThData(A, i+1, r));
//start th 1
void quicksort(int A, int l, int r)
Stack<int> Indexes = new Stack<int>();
push2(Indexes, l, r);
while (Indexes.Count > 0)
l = Indexes.Pop(); r = Indexes.Pop();
if (r <= l) continue;
int i = partition(V, l, r);
push2(Indexes, l, i - 1);
push2(Indexes, i + 1, r);
quicksort(V, 0, V.Length - 1);
int d = 1;
22 seconds to sort 100,000 integers?? Are you running this on an Atari 800? That's horrible performance for a Quicksort.
I've got a Mergesort implementation in my toolbox that'll sort 10,000,000 integers in less than 12 seconds - single threaded.
Windows will not automatically rework your code to run in on multiple cores. No O/S will do that. YOU have to do that my rewriting your code. I'd concentrate on reworking your implementation to get better performance on a single thread first before you start to worry about how you're going to multithread this. Multithreading a poor implementation doesn't get you anything but more threads running poorly.
This quick sort couldn't be so bad. Ok, it is not an optimized QuickSort.
I think it depends also on the input data you provide. I have used other sorting algorithms with these data set and I get comparative results.
I think the stack operations are slowing your algorithm. Quicksort only needs a simple array.
The generic operations that are "array-like" will reallocate a NEW array and copy all the elements to this array when the old array isn't long enough to hold a new element. This gives O(n^2) performance, which is slow. (Quicksort should be O(n log n)).
Using multiple threads to speed Quicksort is a good idea because the partitioning lets the threads work independently, without requiring synchronization. You just have to make sure your basic operations aren't wasting time.
Considering a Quick sort should run about 1,500 times faster than what you're now reporting, you've got major problems. 10,000 integers should take less than 0.01 seconds on todays hardware - single threaded.
I use as test a vector with 100 000 ints. It is ordered in Descending order.
(another problem I have choosed partition element at one end, result in a small partition on a Descending order data set )
I have tried an optimized Insertion and it sorts it in 20s. c++
I think I test the worst case scenario which is N2 for both inserion and quicksort.
In average cases it works super fast, in less than a second;
I got like you with 10 mils of ints around 3 sec.
constint sizeV = 10000000;
Random rnd = new Random();
for (int i = 0; i < sizeV; ++i)
V[i] = rnd.Next(0, 9999999);
modified 18-Jan-13 16:37pm.
Last Visit: 31-Dec-99 18:00 Last Update: 20-Dec-13 0:55