linux-kernel - Re: newidle balancing in NUMA domain?

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Message-ID: <20091130081918.GM17484@wotan.suse.de>
Date:	Mon, 30 Nov 2009 09:19:18 +0100
From:	Nick Piggin <npiggin@...e.de>
To:	Jason Garrett-Glaser <darkshikari@...il.com>
Cc:	Ingo Molnar <mingo@...e.hu>, Peter Zijlstra <peterz@...radead.org>,
	Linux Kernel Mailing List <linux-kernel@...r.kernel.org>
Subject: Re: newidle balancing in NUMA domain?

On Tue, Nov 24, 2009 at 09:24:26AM -0800, Jason Garrett-Glaser wrote:
> > Quite a few being one test case, and on a program with a horrible
> > parallelism design (rapid heavy weight forks to distribute small
> > units of work).
> 
> > If x264 is declared dainbramaged, that's fine with me too.
> 
> We did multiple benchmarks using a thread pool and it did not help.
> If you want to declare our app "braindamaged", feel free, but pooling
> threads to avoid re-creation gave no benefit whatsoever.  If you think
> the parallelism methodology is wrong as a whole, you're basically
> saying that Linux shouldn't be used for video compression, because
> this is the exact same threading model used by almost every single
> video encoder ever made.  There are actually a few that use
> slice-based threading, but those are actually even worse from your
> perspective, because slice-based threading spawns mulitple threads PER
> FRAME instead of one per frame.
> 
> Because of the inter-frame dependencies in video coding it is
> impossible to efficiently get a granularity of more than one thread
> per frame.  Pooling threads doesn't change the fact that you are
> conceptually creating a thread for each frame--it just eliminates the
> pthread_create call.  In theory you could do one thread per group of
> frames, but that is completely unrealistic for real-time encoding
> (e.g. streaming), requires a catastrophically large amount of memory,
> makes it impossible to track the bit buffer, and all other sorts of
> bad stuff.

If you can scale to N threads by having 1 frame per thread, then
you can scale to N/2 threads and have 2 frames per thread. Can't
you?

Is your problem in scaling to a large N?

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