Question

I’m developing an app which one scans thousands copies of a struct; ~1 GB RAM. Speed is important.

     ParallelScan(_from, _to);  //In a new thread

I manually adjust the threads count:

     if (myStructs.Count == 0) { threads = 0; }
     else if (myStructs.Count < 1 * Number.Thousand) { threads = 1; }
     else if (myStructs.Count < 3 * Number.Thousand) { threads = 2; }
     else if (myStructs.Count < 5 * Number.Thousand) { threads = 4; }
     else if (myStructs.Count < 10 * Number.Thousand) { threads = 8; }
     else if (myStructs.Count < 20 * Number.Thousand) { threads = 12; }
     else if (myStructs.Count < 30 * Number.Thousand) { threads = 20; }
     else if (myStructs.Count < 50 * Number.Thousand) { threads = 30; }
     else threads = 40;

I just wrote it from scratch and I need to modify it for another CPU, etc. I think I could write a smarter code which one dynamically starts a new thread if CPU is available at the moment:

• If CPU is not %100 start N thread
• Measure CPU or thread process time & modify/estimate N
• Loop until scan all struct array

Is there anyone think that “I did something similar” or “I have a better idea” ?

UPDATE: The solution

    Parallel.For(0, myStructs.Count - 1, (x) =>
    {
         ParallelScan(x, x); // Will be ParallelScan(x);

    });

I did trim tons of code. Thanks people!

UPDATE 2: Results

Scan time for 10K templates

• 1 Thread: 500 ms
• 10 Threads: 300 ms
• 40 Threads: 600 ms
• Tasks: 100 ms

Answer 1

The standard answer: Use Tasks (TPL) , not Threads. Tasks require Fx4.

Your ParallelScan could just use Parallel.Foreach( ... ) or PLINQ (.AsParallel()).

The TPL framework includes a scheduler, and ForEach() uses a partitioner, to adapt to CPU cores and load. Your problem is most likely solved with the standard components but you can write custom-schedulers and -partitioners.