> From: Paul E. McKenney <paulmck@xxxxxxxxxx>
> [...]
> > Qiuxu also noted impressive boot-time improvements with earlier
> > version of patch. An excerpt from the data he shared:
> >
> > 1) Testing environment:
> > OS : CentOS Stream 8 (non-RT OS)
> > Kernel : v6.2
> > Machine : Intel Cascade Lake server (2 sockets, each with 44 logical
> threads)
> > Qemu args : -cpu host -enable-kvm, -smp 88,threads=2,sockets=2,
> > …
> >
> > 2) OS boot time definition:
> > The time from the start of the kernel boot to the shell command line
> > prompt is shown from the console. [ Different people may have
> > different OS boot time definitions. ]
> >
> > 3) Measurement method (very rough method):
> > A timer in the kernel periodically prints the boot time every 100ms.
> > As soon as the shell command line prompt is shown from the console,
> > we record the boot time printed by the timer, then the printed boot
> > time is the OS boot time.
> >
> > 4) Measured OS boot time (in seconds)
> > a) Measured 10 times w/o this patch:
> > 8.7s, 8.4s, 8.6s, 8.2s, 9.0s, 8.7s, 8.8s, 9.3s, 8.8s, 8.3s
> > The average OS boot time was: ~8.7s
> >
> > b) Measure 10 times w/ this patch:
> > 8.5s, 8.2s, 7.6s, 8.2s, 8.7s, 8.2s, 7.8s, 8.2s, 9.3s, 8.4s
> > The average OS boot time was: ~8.3s.
>
> Unfortunately, given that a's average is within one standard deviation of b's
> average, this is most definitely not statistically significant.
> Especially given only ten measurements for each case -- you need *at*
> *least* 24, preferably more. Especially in this case, where you don't really
> know what the underlying distribution is.
Thank you so much Paul for the detailed comments on the measured data.
I'm curious how did you figure out the number 24 that we at *least* need.
This can guide me on whether the number of samples is enough for
future testing ;-).
I did another 48 measurements (2x of 24) for each case
(w/o and w/ Joel's v2 patch) as below.
All the testing configurations for the new testing
are the same as before.
a) Measured 48 times w/o v2 patch (in seconds):
8.4, 8.8, 9.2, 9.0, 8.3, 9.6, 8.8, 9.4,
8.7, 9.2, 8.3, 9.4, 8.4, 9.6, 8.5, 8.8,
8.8, 8.9, 9.3, 9.2, 8.6, 9.7, 9.2, 8.8,
8.7, 9.0, 9.1, 9.5, 8.6, 8.9, 9.1, 8.6,
8.2, 9.1, 8.8, 9.2, 9.1, 8.9, 8.4, 9.0,
9.8, 9.8, 8.7, 8.8, 9.1, 9.5, 9.5, 8.7
The average OS boot time was: ~9.0s
b) Measure 48 times w/ v2 patch (in seconds):
7.7, 8.6, 8.1, 7.8, 8.2, 8.2, 8.8, 8.2,
9.8, 8.0, 9.2, 8.8, 9.2, 8.5, 8.4, 9.2,
8.5, 8.3, 8.1, 8.3, 8.6, 7.9, 8.3, 8.3,
8.6, 8.9, 8.0, 8.5, 8.4, 8.6, 8.7, 8.0,
8.8, 8.8, 9.1, 7.9, 9.7, 7.9, 8.2, 7.8,
8.1, 8.5, 8.6, 8.4, 9.2, 8.6, 9.6, 8.3,
The average OS boot time was: ~8.5s
@Joel Fernandes (Google), you may replace my old data with the above
new data in your commit message.
> But we can apply the binomial distribution instead of the usual normal
> distribution. First, let's sort and take the medians:
>
> a: 8.2 8.3 8.4 8.6 8.7 8.7 8.8 8.8 9.0 9.3 Median: 8.7
> b: 7.6 7.8 8.2 8.2 8.2 8.2 8.4 8.5 8.7 9.3 Median: 8.2
>
> 8/10 of a's data points are greater than 0.1 more than b's median and 8/10
> of b's data points are less than 0.1 less than a's median.
> What are the odds that this happens by random chance?
>
> This is given by sum_0^2 (0.5^10 * binomial(10,i)), which is about 0.055.
What's the meaning of 0.5 here? Was it the probability (we assume?) that
each time b's data point failed (or didn't satisfy) "less than 0.1 less than
a's median"?
> This is not quite 95% confidence, so not hugely convincing, but it is at least
> close. Not that this is the confidence that (b) is 100ms faster than (a), not
> just that (b) is faster than (a).
>
> Not sure that this really carries its weight, but in contrast to the usual
> statistics based on the normal distribution, it does suggest at least a little
> improvement. On the other hand, anyone who has carefully studied
> nonparametric statistics probably jumped out of the boat several paragraphs
> ago. ;-)
>
> A few more questions interspersed below.
>
> Thanx, Paul
>
> > Tested-by: Qiuxu Zhuo <qiuxu.zhuo@xxxxxxxxx>
> > Signed-off-by: Joel Fernandes (Google) <joel@xxxxxxxxxxxxxxxxx>
