Re: [PATCH v3 00/15] mm/memory: optimize fork() with PTE-mapped THP

[David Hildenbrand]

> > 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.

Better use a system where people will actually run Linux production 
workloads on, even if it is slower :)

[...]

> > > 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.

Hopefully you were just staring at the wrong numbers (e.g., only with 
fork patches). Because both (munmap/pte-dontneed) are using the exact 
same code path.

--
Cheers,

David / dhildenb