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Message-ID: <CAOUHufaWbWZ-q-PUJnjXD_jDk1s34mcg4vHU8CtAtmeAT-deRA@mail.gmail.com>
Date: Sun, 18 Jun 2023 14:11:11 -0600
From: Yu Zhao <yuzhao@...gle.com>
To: Marc Zyngier <maz@...nel.org>
Cc: Andrew Morton <akpm@...ux-foundation.org>,
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Subject: Re: kvm/arm64: Spark benchmark
On Fri, Jun 9, 2023 at 7:04 AM Marc Zyngier <maz@...nel.org> wrote:
>
> On Fri, 09 Jun 2023 01:59:35 +0100,
> Yu Zhao <yuzhao@...gle.com> wrote:
> >
> > TLDR
> > ====
> > Apache Spark spent 12% less time sorting four billion random integers twenty times (in ~4 hours) after this patchset [1].
>
> Why are the 3 architectures you have considered being evaluated with 3
> different benchmarks?
I was hoping people having special interests in different archs might
try to reproduce the benchmarks that I didn't report (but did cover)
and see what happens.
> I am not suspecting you to have cherry-picked
> the best results
I'm generally very conservative when reporting *synthetic* results.
For example, the same memcached benchmark used on powerpc yielded >50%
improvement on aarch64, because the default Ubuntu Kconfig uses 64KB
base page size for powerpc but 4KB for aarch64. (Before the series,
the reclaim (swap) path takes kvm->mmu_lock for *write* on O(nr of all
pages to consider); after the series, it becomes O(actual nr of pages
to swap), which is <10% given how the benchmark was set up.)
Ops/sec Avg. Latency p50 Latency p99 Latency p99.9 Latency
------------------------------------------------------------------------
Before 639511.40 0.09940 0.04700 0.27100 22.52700
After 974184.60 0.06471 0.04700 0.15900 3.75900
> but I'd really like to see a variety of benchmarks
> that exercise this stuff differently.
I'd be happy to try other synthetic workloads that people think that
are relatively representative. Also, I've backported the series and
started an A/B experiment involving ~1 million devices (real-world
workloads). We should have the preliminary results by the time I post
the next version.
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