linux-kernel - Re: [PATCH] KVM: x86: Reduce retpoline performance impact in slot_handle_level

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Message-ID: <20180205085124.GF2249@hirez.programming.kicks-ass.net>
Date:   Mon, 5 Feb 2018 09:51:24 +0100
From:   Peter Zijlstra <peterz@...radead.org>
To:     David Woodhouse <dwmw2@...radead.org>
Cc:     Alan Cox <gnomes@...rguk.ukuu.org.uk>,
        Linus Torvalds <torvalds@...ux-foundation.org>,
        Thomas Gleixner <tglx@...utronix.de>,
        KarimAllah Ahmed <karahmed@...zon.de>, sironi@...zon.de,
        the arch/x86 maintainers <x86@...nel.org>,
        KVM list <kvm@...r.kernel.org>,
        Paolo Bonzini <pbonzini@...hat.com>,
        Linux Kernel Mailing List <linux-kernel@...r.kernel.org>,
        Borislav Petkov <bp@...en8.de>, Paul Turner <pjt@...gle.com>
Subject: Re: [PATCH] KVM: x86: Reduce retpoline performance impact in
 slot_handle_level_range()

On Sat, Feb 03, 2018 at 02:46:47PM +0000, David Woodhouse wrote:
> > For the simple case how about wrapping the if into
> > 
> >                 call_likely(foo->bar, usualfunction, args)
> > 
> > as a companion to 
> > 
> >                  foo->bar(args)
> > 
> > that can resolve to nothing special on architectures that don't need it,
> > an if/else case on platforms with spectre, and potentially clever
> > stuff on any platform where you can beat the compiler by knowing
> > probabilities it can't infer ?
> 
> Yeah. I'm keen on being able to use something like alternatives to
> *change* 'usualfunction' at runtime though. I suspect it'll be a win
> for stuff like dma_ops.
> 
> But I'm also keen to actually base such things on real data, not just
> go randomly "optimising" stuff just because we can. Let's try to make
> sure we fix up the real bottlenecks, and not just go crazy.

Google has a fairly long history of using feedback driven optimization
compiles for the kernel. They were also the ones that developed perf
autofdo tooling IIRC.

https://gcc.gnu.org/wiki/AutoFDO/Tutorial

One of the things pjt promised was a series of patches doing the
proposed optimization for the scheduler code based on their results.