I wrote a naive Parallel.For() loop in C#, shown below. I also did the same work using a regular for() loop to compare single-thread vs. multi-thread. The single thread version took about five seconds every time I ran it. The parallel version took about three seconds at first, but if I ran it about four times, it would slow down dramatically. Most often it took about thirty seconds. One time it took eighty seconds. If I restarted the program, the parallel version would start out fast again, but slow down after three or four parallel runs. Sometimes the parallel runs would speed up again to the original three seconds then slow down.
I wrote another Parallel.For() loop for computing Mandelbrot set members (discarding the results) because I figured that the problem might be related to memory issues allocating and manipulating a large array. The Parallel.For() implementation of this second problem does indeed execute faster than the single-thread version every time, and the times are consistent too.
What data should I be looking at to understand to understand why my first naive program slows down after a number of runs? Is there something in Perfmon I should be looking at? I still suspect it is memory related, but I allocate the array outside the timer. I also tried a GC.Collect() at the end of each run, but that didn't seem help, not consistently anyway. Might it be an alignment issue with cache somewhere on the processor? How would I figure that out? Is there anything else that might be the cause?
JR
const int _meg = 1024 * 1024;
const int _len = 1024 * _meg;
private void ParallelArray() {
int[] stuff = new int[_meg];
System.Diagnostics.Stopwatch s = new System.Diagnostics.Stopwatch();
lblStart.Content = DateTime.Now.ToString();
s.Start();
Parallel.For(0,
_len,
i => {
stuff[i % _meg] = i;
}
);
s.Stop();
lblResult.Content = DateTime.Now.ToString();
lblDiff.Content = s.ElapsedMilliseconds.ToString();
}
