Re: Linux 5.19-rc8

[Russell King (Oracle)]

On Tue, Jul 26, 2022 at 06:33:55PM -0700, Yury Norov wrote:
> On Tue, Jul 26, 2022 at 5:15 PM Russell King (Oracle)
> <linux@xxxxxxxxxxxxxxx> wrote:
> >
> > On Tue, Jul 26, 2022 at 01:20:23PM -0700, Linus Torvalds wrote:
> > > On Tue, Jul 26, 2022 at 12:44 PM Russell King (Oracle)
> > > <linux@xxxxxxxxxxxxxxx> wrote:
> > > >
> > > > Overall, I would say it's pretty similar (some generic perform
> > > > marginally better, some native perform marginally better) with the
> > > > exception of find_first_bit() being much better with the generic
> > > > implementation, but find_next_zero_bit() being noticably worse.
> > >
> > > The generic _find_first_bit() code is actually sane and simple. It
> > > loops over words until it finds a non-zero one, and then does trivial
> > > calculations on that last word.
> > >
> > > That explains why the generic code does so much better than your byte-wise asm.
> > >
> > > In contrast, the generic _find_next_bit() I find almost offensively
> > > silly - which in turn explains why your byte-wide asm does better.
> > >
> > > I think the generic _find_next_bit() should actually do what the m68k
> > > find_next_bit code does: handle the first special word itself, and
> > > then just call find_first_bit() on the rest of it.
> > >
> > > And it should *not* try to handle the dynamic "bswap and/or bit sense
> > > invert" thing at all. That should be just four different (trivial)
> > > cases for the first word.
> >
> > Here's the results for the native version converted to use word loads:
> >
> > [   37.319937]
> >                Start testing find_bit() with random-filled bitmap
> > [   37.330289] find_next_bit:                 2222703 ns, 163781 iterations
> > [   37.339186] find_next_zero_bit:            2154375 ns, 163900 iterations
> > [   37.348118] find_last_bit:                 2208104 ns, 163780 iterations
> > [   37.372564] find_first_bit:               17722203 ns,  16370 iterations
> > [   37.737415] find_first_and_bit:          358135191 ns,  32453 iterations
> > [   37.745420] find_next_and_bit:             1280537 ns,  73644 iterations
> > [   37.752143]
> >                Start testing find_bit() with sparse bitmap
> > [   37.759032] find_next_bit:                   41256 ns,    655 iterations
> > [   37.769905] find_next_zero_bit:            4148410 ns, 327026 iterations
> > [   37.776675] find_last_bit:                   48742 ns,    655 iterations
> > [   37.790961] find_first_bit:                7562371 ns,    655 iterations
> > [   37.797743] find_first_and_bit:              47366 ns,      1 iterations
> > [   37.804527] find_next_and_bit:               59924 ns,      1 iterations
> >
> > which is generally faster than the generic version, with the exception
> > of the sparse find_first_bit (generic was:
> > [   25.657304] find_first_bit:                7328573 ns,    656 iterations)
> >
> > find_next_{,zero_}bit() in the sparse case are quite a bit faster than
> > the generic code.
> 
> Look at find_{first,next}_and_bit results. Those two have no arch version
> and in both cases use generic code. In theory they should be equally fast
> before and after, but your testing says that generic case is slower even
> for them, and the difference is comparable with real arch functions numbers.
> It makes me feel like:
>  - there's something unrelated, like governor/throttling that affect results;
>  - the numbers are identical, taking the dispersion into account.
> 
> If the difference really concerns you, I'd suggest running the test
> several times
> to measure confidence intervals.

Given that the benchmark is run against random bitmaps and with
interrupts enabled, there is going to be noise in the results.

Here's the second run:

[26234.429389]
               Start testing find_bit() with random-filled bitmap
[26234.439722] find_next_bit:                 2206687 ns, 164277 iterations
[26234.448664] find_next_zero_bit:            2188368 ns, 163404 iterations
[26234.457612] find_last_bit:                 2223742 ns, 164278 iterations
[26234.482056] find_first_bit:               17720726 ns,  16384 iterations
[26234.859374] find_first_and_bit:          370602019 ns,  32877 iterations
[26234.867379] find_next_and_bit:             1280651 ns,  74091 iterations
[26234.874107]
               Start testing find_bit() with sparse bitmap
[26234.881014] find_next_bit:                   46142 ns,    656 iterations
[26234.891900] find_next_zero_bit:            4158987 ns, 327025 iterations
[26234.898672] find_last_bit:                   49727 ns,    656 iterations
[26234.912504] find_first_bit:                7107862 ns,    656 iterations
[26234.919290] find_first_and_bit:              52092 ns,      1 iterations
[26234.926076] find_next_and_bit:               60856 ns,      1 iterations

And a third run:

[26459.679524]
               Start testing find_bit() with random-filled bitmap
[26459.689871] find_next_bit:                 2199418 ns, 163311 iterations
[26459.698798] find_next_zero_bit:            2181289 ns, 164370 iterations
[26459.707738] find_last_bit:                 2213638 ns, 163311 iterations
[26459.732224] find_first_bit:               17764152 ns,  16429 iterations
[26460.133823] find_first_and_bit:          394886375 ns,  32672 iterations
[26460.141818] find_next_and_bit:             1269693 ns,  73485 iterations
[26460.148545]
               Start testing find_bit() with sparse bitmap
[26460.155433] find_next_bit:                   40753 ns,    653 iterations
[26460.166307] find_next_zero_bit:            4148211 ns, 327028 iterations
[26460.173078] find_last_bit:                   50017 ns,    653 iterations
[26460.187007] find_first_bit:                7205325 ns,    653 iterations
[26460.193790] find_first_and_bit:              49358 ns,      1 iterations
[26460.200577] find_next_and_bit:               62332 ns,      1 iterations

My gut feeling is that yes, there is some variance, but not on an
order that is significant that would allow us to say "there's no
difference".

find_next_bit results for random are: 2222703, 2206687, 2199418,
which is an average of 2209603 and a variance of around 0.5%.
The difference between this and the single generic figure I have
is on the order of 20%.

I'll do the same with find_first_bit for random: 17722203, 17720726,
and 17764152. Average is 17735694. Variance is around 0.1% or 0.2%.
The difference between this and the single generic figure I have is
on the order of 5%. Not so large, but still quite a big difference
compared to the variance.

find_first_bit for sparse: 7562371, 7107862, 7205325. Average is
7291853. Variance is higher at about 4%. Difference between this and
the generic figure is 0.5%, so this one is not significantly
different.

The best result looks to be find_next_zero_bit for the sparse bitmap
case. The generic code measures 5.5ms, the native code is sitting
around 4.1ms. That's a difference of around 34%, and by just looking
at the range in the figures above we can see this is a significant
result without needing to do the calculations. Similar is true of
find_next_bit for the sparse bitmap.

So, I think the results are significant in most cases and variance
doesn't account for the differences. The only one which isn't is
find_first_bit for the sparse case.

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