Would it be possible to get the data for older runs back, so that
it's easier to find the changes which caused the slowdown ?

Unfortunately no. The reasons are that that data was misleading because different points were computed with a different version of pyperformance and therefore with different packages (and therefore different code). So the points could not be compared among themselves.

Also, past data didn't include 3.9 commits because the data gathering was not automated and it didn't run in a long time :(

On Wed, 14 Oct 2020 at 14:57, M.-A. Lemburg <mal@egenix.com> wrote:
Hi Pablo,

thanks for pointing this out.

Would it be possible to get the data for older runs back, so that
it's easier to find the changes which caused the slowdown ?

Going to the timeline, it seems that the system only has data
for Oct 14 (today):


In addition to unpack_sequence, the regex_dna test has slowed
down a lot compared to Py3.8.



On 14.10.2020 15:16, Pablo Galindo Salgado wrote:
> Hi!
> I have updated the branch benchmarks in the pyperformance server and now they
> include 3.9. There are
> some benchmarks that are faster but on the other hand some benchmarks are
> substantially slower, pointing
> at a possible performance regression in 3.9 in some aspects. In particular some
> tests like "unpack sequence" are
> almost 20% slower. As there are some other tests were 3.9 is faster, is not fair
> to conclude that 3.9 is slower, but
> this is something we should look into in my opinion.
> You can check these benchmarks I am talking about by:
> * Go here: https://speed.python.org/comparison/
> * In the left bar, select "lto-pgo latest in branch '3.9'" and "lto-pgo latest
> in branch '3.8'"
> * To better read the plot, I would recommend to select a "Normalization" to the
> 3.8 branch (this is in the top part of the page)
>    and to check the "horizontal" checkbox.
> These benchmarks are very stable: I have executed them several times over the
> weekend yielding the same results and,
> more importantly, they are being executed on a server specially prepared to
> running reproducible benchmarks: CPU affinity,
> CPU isolation, CPU pinning for NUMA nodes, CPU frequency is fixed, CPU governor
> set to performance mode, IRQ affinity is
> disabled for the benchmarking CPU nodes...etc so you can trust these numbers.
> I kindly suggest for everyone interested in trying to improve the 3.9 (and
> master) performance, to review these benchmarks
> and try to identify the problems and fix them or to find what changes introduced
> the regressions in the first place. All benchmarks
> are the ones being executed by the pyperformance suite
> (https://github.com/python/pyperformance) so you can execute them
> locally if you need to.
> ---
> On a related note, I am also working on the speed.python.org
> <http://speed.python.org> server to provide more automation and
> ideally some integrations with GitHub to detect performance regressions. For
> now, I have done the following:
> * Recompute benchmarks for all branches using the same version of
> pyperformance (except master) so they can
>    be compared with each other. This can only be seen in the "Comparison"
> tab: https://speed.python.org/comparison/
> * I am setting daily builds of the master branch so we can detect performance
> regressions with daily granularity. These
>    daily builds will be located in the "Changes" and "Timeline" tabs
> (https://speed.python.org/timeline/).
> * Once the daily builds are working as expected, I plan to work on trying to
> automatically comment or PRs or on bpo if
> we detect that a commit has introduced some notable performance regression.
> Regards from sunny London,
> Pablo Galindo Salgado.
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