== Quote from dsimcha (dsim...@yahoo.com)'s article > == Quote from Dan (dsstruth...@yahoo.com)'s article > > I have a question regarding performance issue I am seeing on multicore > > Windows > systems. I am creating many threads to do parallel tasks, and on multicore > Windows systems the performance is abysmal. If I use task manager to set the > processor affinity to a single CPU, the program runs as I would expect. > Without > that, it takes about 10 times as long to complete. > > Am I doing something wrong? I have tried DMD 2.0.37 and DMD 1.0.53 with the > same results, running the binary on both a dual-core P4 and a newer Core2 duo. > > Any help is greatly appreciated! > I've seen this happen before. Without knowing the details of your code, my > best > guess is that you're getting a lot of contention for the GC lock. (It could > also > be some other lock, but if it were, there's a good chance you'd already know > it > because it wouldn't be hidden.) The current GC design isn't very > multithreading-friendly yet. It requires a lock on every allocation. > Furthermore, the array append operator (~=) currently takes the GC lock on > **every > append** to query the GC for info about the memory block that the array > points to. > There's been plenty of talk about what should be done to eliminate this, but > nothing has been implemented so far. > Assuming I am right about why your code is so slow, here's how to deal with > it: > 1. Cut down on unnecessary memory allocations. Use structs instead of > classes > where it makes sense. > 2. Try to stack allocate stuff. alloca is your friend. > 3. Pre-allocate arrays if you know ahead of time how long they're supposed > to be. > If you don't know how long they're supposed to be, use std.array.Appender > (in D2) > for now until a better solution gets implemented. Never use ~= in > multithreaded > code that gets executed a lot.
Yes, I've seen this before, too. But in my muti-threads, the alloc operations aren't avoiding, so the D's GC should improve it's performance for multi-threads.
