The performance figures in the Python 3.9 "What's New"
Those are also micro-benchmarks, which can have no effect at all on macro-benchmarks. The ones I am linking are almost all macro-benchmarks, so, unfortunately, the ones in Python 3.9 "What's New" are not lying and they seem to be correlated to the same issue.
Also although they are not incorrect, those benchmarks in the Python 3.9 "What's New" were not executed with LTO/PGO/CPU isolation...etc so I would kindly suggest taking the ones in the speed.python.org as the canonical ones if they start to differ in any way.
Pablo
On Wed, 14 Oct 2020 at 14:25, Paul Moore <p.f.moore@gmail.com> wrote:
The performance figures in the Python 3.9 "What's New" (here - https://docs.python.org/3/whatsnew/3.9.html#optimizations) did look oddly like a lot of things went slower, to me. I assumed I'd misread the figures, and moved on, but maybe I was wrong to do so...
Paul
On Wed, 14 Oct 2020 at 14:17, Pablo Galindo Salgado <pablogsal@gmail.com> wrote:
Hi!
I have updated the branch benchmarks in the pyperformance server and now
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
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 server to
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
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
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
they include 3.9. There are particular some tests like "unpack sequence" are provide more automation and pyperformance (except master) so they can performance regressions with daily granularity. These 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.
python-committers mailing list -- python-committers@python.org To unsubscribe send an email to python-committers-leave@python.org https://mail.python.org/mailman3/lists/python-committers.python.org/ Message archived at https://mail.python.org/archives/list/python-committers@python.org/message/G... Code of Conduct: https://www.python.org/psf/codeofconduct/