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Date:   Sun, 28 Apr 2019 14:17:21 +0200
From:   Ingo Molnar <mingo@kernel.org>
To:     Aubrey Li <aubrey.intel@gmail.com>
Cc:     Julien Desfossez <jdesfossez@digitalocean.com>,
        Vineeth Remanan Pillai <vpillai@digitalocean.com>,
        Nishanth Aravamudan <naravamudan@digitalocean.com>,
        Peter Zijlstra <peterz@infradead.org>,
        Tim Chen <tim.c.chen@linux.intel.com>,
        Thomas Gleixner <tglx@linutronix.de>,
        Paul Turner <pjt@google.com>,
        Linus Torvalds <torvalds@linux-foundation.org>,
        Linux List Kernel Mailing <linux-kernel@vger.kernel.org>,
        Subhra Mazumdar <subhra.mazumdar@oracle.com>,
        =?iso-8859-1?Q?Fr=E9d=E9ric?= Weisbecker <fweisbec@gmail.com>,
        Kees Cook <keescook@chromium.org>,
        Greg Kerr <kerrnel@google.com>, Phil Auld <pauld@redhat.com>,
        Aaron Lu <aaron.lwe@gmail.com>,
        Valentin Schneider <valentin.schneider@arm.com>,
        Mel Gorman <mgorman@techsingularity.net>,
        Pawan Gupta <pawan.kumar.gupta@linux.intel.com>,
        Paolo Bonzini <pbonzini@redhat.com>
Subject: Re: [RFC PATCH v2 00/17] Core scheduling v2
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* Aubrey Li <aubrey.intel@gmail.com> wrote:

> On Sun, Apr 28, 2019 at 5:33 PM Ingo Molnar <mingo@kernel.org> wrote:
> > So because I'm a big fan of presenting data in a readable fashion, here
> > are your results, tabulated:
> 
> I thought I tried my best to make it readable, but this one looks much better,
> thanks, ;-)
> >
> >  #
> >  # Sysbench throughput comparison of 3 different kernels at different
> >  # load levels, higher numbers are better:
> >  #
> >
> >  .--------------------------------------|----------------------------------------------------------------.
> >  |  NA/AVX     vanilla-SMT    [stddev%] |coresched-SMT   [stddev%]   +/-  |   no-SMT    [stddev%]   +/-  |
> >  |--------------------------------------|----------------------------------------------------------------|
> >  |   1/1             508.5    [  0.2% ] |        504.7   [  1.1% ]   0.8% |    509.0    [  0.2% ]   0.1% |
> >  |   2/2            1000.2    [  1.4% ] |       1004.1   [  1.6% ]   0.4% |    997.6    [  1.2% ]   0.3% |
> >  |   4/4            1912.1    [  1.0% ] |       1904.2   [  1.1% ]   0.4% |   1914.9    [  1.3% ]   0.1% |
> >  |   8/8            3753.5    [  0.3% ] |       3748.2   [  0.3% ]   0.1% |   3751.3    [  0.4% ]   0.1% |
> >  |  16/16           7139.3    [  2.4% ] |       7137.9   [  1.8% ]   0.0% |   7049.2    [  2.4% ]   1.3% |
> >  |  32/32          10899.0    [  4.2% ] |      10780.3   [  4.4% ]  -1.1% |  10339.2    [  9.6% ]  -5.1% |
> >  |  64/64          15086.1    [ 11.5% ] |      14262.0   [  8.2% ]  -5.5% |  11168.7    [ 22.2% ] -26.0% |
> >  | 128/128         15371.9    [ 22.0% ] |      14675.8   [ 14.4% ]  -4.5% |  10963.9    [ 18.5% ] -28.7% |
> >  | 256/256         15990.8    [ 22.0% ] |      12227.9   [ 10.3% ] -23.5% |  10469.9    [ 19.6% ] -34.5% |
> >  '--------------------------------------|----------------------------------------------------------------'
> >
> > One major thing that sticks out is that if we compare the stddev numbers
> > to the +/- comparisons then it's pretty clear that the benchmarks are
> > very noisy: in all but the last row stddev is actually higher than the
> > measured effect.
> >
> > So what does 'stddev' mean here, exactly? The stddev of multipe runs,
> > i.e. measured run-to-run variance? Or is it some internal metric of the
> > benchmark?
> >
> 
> The benchmark periodically reports intermediate statistics in one second,
> the raw log looks like below:
> [ 11s ] thds: 256 eps: 14346.72 lat (ms,95%): 44.17
> [ 12s ] thds: 256 eps: 14328.45 lat (ms,95%): 44.17
> [ 13s ] thds: 256 eps: 13773.06 lat (ms,95%): 43.39
> [ 14s ] thds: 256 eps: 13752.31 lat (ms,95%): 43.39
> [ 15s ] thds: 256 eps: 15362.79 lat (ms,95%): 43.39
> [ 16s ] thds: 256 eps: 26580.65 lat (ms,95%): 35.59
> [ 17s ] thds: 256 eps: 15011.78 lat (ms,95%): 36.89
> [ 18s ] thds: 256 eps: 15025.78 lat (ms,95%): 39.65
> [ 19s ] thds: 256 eps: 15350.87 lat (ms,95%): 39.65
> [ 20s ] thds: 256 eps: 15491.70 lat (ms,95%): 36.89
> 
> I have a python script to parse eps(events per second) and lat(latency)
> out, and compute the average and stddev. (And I can draw a curve locally).
> 
> It's noisy indeed when tasks number is greater than the CPU number.
> It's probably caused by high frequent load balance and context switch.

Ok, so it's basically an internal workload noise metric, it doesn't 
represent the run-to-run noise.

So it's the real stddev of the workload - but we don't know whether the 
measured performance figure is exactly in the middle of the runtime 
probability distribution.

> Do you have any suggestions? Or any other information I can provide?

Yeah, so we don't just want to know the "standard deviation" of the 
measured throughput values, but also the "standard error of the mean".

I suspect it's pretty low, below 1% for all rows?

Thanks,

	Ingo