Messages in this thread | | | From | Bill Wendling <> | Date | Fri, 2 Jul 2021 05:46:46 -0700 | Subject | Re: [GIT PULL] Clang feature updates for v5.14-rc1 |
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On Tue, Jun 29, 2021 at 2:04 PM Linus Torvalds <torvalds@linux-foundation.org> wrote: > > On Tue, Jun 29, 2021 at 1:44 PM Kees Cook <keescook@chromium.org> wrote: > > > > > > And it causes the kernel to be bigger and run slower. > > > > Right -- that's expected. It's not designed to be the final kernel > > someone uses. :) > > Well, from what I've seen, you actually want to run real loads in > production environments for PGO to actually be anything but a bogus > "performance benchmarks only" kind of thing. > The reason we use PGO in this way is because we _cannot_ release a kernel into production that hasn't had PGO applied to it. The performance of a non-PGO'ed kernel is a non-starter for rollout. We try our best to replicate this environment for the benchmarks, which is the only sane way to do this. I can't imagine that we're the only ones who run up against this chicken-and-egg problem.
For why we don't use sampling, PGO gives a better performance boost from an instrumented kernel rather than a sampled profile. I'll work on getting statistics to show this.
-bw
> Of course, "performance benchmarks only" is very traditional, and > we've seen that used over and over in the past in this industry. That > doesn't make it _right_, though. > > And if you actually want to have it usable in production environments, > you really should strive to run code as closely as possible to a > production kernel too. > > You'd want to run something that you can sample over time, and in > production, not something that you have to build a special kernels for > that then gets used for a benchmark run, but can't be kept in > production because it performs so much worse. > > Real proper profiles will tell you what *really* matters - and if you > don't have enough samples to give you good information, then that > particular code clearly is not important enough to waste PGO on. > > This is not all that dissimilar to using gprof information for > traditional - manual - optimizations. > > Sure, instrumented gprof output is better than nothing, but it is > *hugely* worse than actual proper sampled profiles that actually show > what matters for performance (as opposed to what runs a lot - the two > are not necessarily all that closely correlated, with cache misses > being a thing). > > And I really hate how pretty much all of the PGO support seems to be > just about this inferior method of getting the data. > > Linus
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