On 31/01/2024 13:38, David Hildenbrand wrote:

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Nope: looks the same. I've taken my test harness out of the picture and done
everything manually from the ground up, with the old tests and the new.
Headline
is that I see similar numbers from both.

I took me a while to get really reproducible numbers on Intel. Most importantly:
* Set a fixed CPU frequency, disabling any boost and avoiding any
   thermal throttling.
* Pin the test to CPUs and set a nice level.

I'm already pinning the test to cpu 0. But for M2, at least, I'm running in a VM
on top of macos, and I don't have a mechanism to pin the QEMU threads to the
physical CPUs. Anyway, I don't think these are problems because for a given
kernel build I can accurately repro numbers.

Oh, you do have a layer of virtualization in there. I *suspect* that might
amplify some odd things regarding code layout, caching effects, etc.

I guess especially the fork() benchmark is too sensible (fast) for things like
that, so I would just focus on bare metal results where you can control the
environment completely.

Yeah, maybe. OK I'll park M2 for now.

Note that regarding NUMA effects, I mean when some memory access within the same
socket is faster/slower even with only a single node. On AMD EPYC that's
possible, depending on which core you are running and on which memory controller
the memory you want to access is located. If both are in different quadrants
IIUC, the access latency will be different.

I've configured the NUMA to only bring the RAM and CPUs for a single socket
online, so I shouldn't be seeing any of these effects. Anyway, I've been using
the Altra as a secondary because its so much slower than the M2. Let me move
over to it and see if everything looks more straightforward there.

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But yes: I was observing something similar on AMD EPYC, where you get
consecutive pages from the buddy, but once you allocate from the PCP it might no
longer be consecutive.

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   - test is 5-10% slower when output is printed to terminal vs when
redirected to
     file. I've always effectively been redirecting. Not sure if this overhead
     could start to dominate the regression and that's why you don't see it?

That's weird, because we don't print while measuring? Anyhow, 5/10% variance on
some system is not the end of the world.

I imagine its cache effects? More work to do to print the output could be
evicting some code that's in the benchmark path?

Maybe. Do you also see these oddities on the bare metal system?

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I'm inclined to run this test for the last N kernel releases and if the number
moves around significantly, conclude that these tests don't really matter.
Otherwise its an exercise in randomly refactoring code until it works well, but
that's just overfitting to the compiler and hw. What do you think?

Personally, I wouldn't lose sleep if you see weird, unexplainable behavior on
some system (not even architecture!). Trying to optimize for that would indeed
be random refactorings.

But I would not be so fast to say that "these tests don't really matter" and
then go wild and degrade them as much as you want. There are use cases that care
about fork performance especially with order-0 pages -- such as Redis.

Indeed. But also remember that my fork baseline time is ~2.5ms, and I think you
said yours was 14ms :)

Yes, no idea why M2 is that fast (BTW, which page size? 4k or 16k? ) :)

The guest kernel is using 4K pages. I'm not quite sure what is happening at
stage2; QEMU doesn't expose any options to explicitly request huge pages for
macos AFAICT.

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I'll continue to mess around with it until the end of the day. But I'm not
making any headway, then I'll change tack; I'll just measure the performance of
my contpte changes using your fork/zap stuff as the baseline and post based on
that.

You should likely not focus on M2 results. Just pick a representative bare metal
machine where you get consistent, explainable results.

Nothing in the code is fine-tuned for a particular architecture so far, only
order-0 handling is kept separate.

BTW: I see the exact same speedups for dontneed that I see for munmap. For
example, for order-9, it goes from 0.023412s -> 0.009785, so -58%. So I'm
curious why you see a speedup for munmap but not for dontneed.

Ugh... ok, coming up.


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