Would it be possible instead to run git-bisect for only a _particular_ benchmark? It seems that may be all that’s needed to track down particular regressions. Also, if e.g. git-bisect is used it wouldn’t be every e.g. 10th revision but rather O(log(n)) revisions.
That only works if there is a single change that produced the issue and not many small changes that have a cumulative effect, which is normally the case. Also, it does not work (is more tricky to make it work) if the issue was introduced, then fixed somehow and then introduced again or in a worse way.
On Wed, 14 Oct 2020 at 18:58, Chris Jerdonek <chris.jerdonek@gmail.com> wrote:
MOn Wed, Oct 14, 2020 at 8:03 AM Pablo Galindo Salgado < pablogsal@gmail.com> wrote:
Would it be possible rerun the tests with the current setup for say the last 1000 revisions or perhaps a subset of these (e.g. every 10th revision) to try to binary search for the revision which introduced the change ?
Every run takes 1-2 h so doing 1000 would be certainly time-consuming :)
Would it be possible instead to run git-bisect for only a _particular_ benchmark? It seems that may be all that’s needed to track down particular regressions. Also, if e.g. git-bisect is used it wouldn’t be every e.g. 10th revision but rather O(log(n)) revisions.
—Chris
That's why from now on I am trying to invest in daily builds for master,
so we can answer that exact question if we detect regressions in the future.
On Wed, 14 Oct 2020 at 15:04, M.-A. Lemburg <mal@egenix.com> wrote:
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
therefore with different packages (and therefore different code). So
On 14.10.2020 16:00, Pablo Galindo Salgado wrote: pyperformance and 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 :(
Make sense.
Would it be possible rerun the tests with the current setup for say the last 1000 revisions or perhaps a subset of these (e.g. every 10th revision) to try to binary search for the revision which introduced the change ?
On Wed, 14 Oct 2020 at 14:57, M.-A. Lemburg <mal@egenix.com <mailto: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.https://github.com/python/pyperformance/blob/master/pyperformance/benchmarks...
https://github.com/python/pyperformance/blob/master/pyperformance/benchmarks...
Thanks. On 14.10.2020 15:16, Pablo Galindo Salgado wrote: > Hi! > > I have updated the branch benchmarks in the pyperformance serverand now they
> include 3.9. There are > some benchmarks that are faster but on the other hand somebenchmarks are
> substantially slower, pointing > at a possible performance regression in 3.9 in some aspects. Inparticular
some > tests like "unpack sequence" are > almost 20% slower. As there are some other tests were 3.9 isfaster, 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 severaltimes over the
> weekend yielding the same results and, > more importantly, they are being executed on a server speciallyprepared to
> running reproducible benchmarks: CPU affinity, > CPU isolation, CPU pinning for NUMA nodes, CPU frequency isfixed, CPU
governor > set to performance mode, IRQ affinity is > disabled for the benchmarking CPU nodes...etc so you can trustthese numbers.
> > I kindly suggest for everyone interested in trying to improvethe 3.9 (and
> master) performance, to review these benchmarks > and try to identify the problems and fix them or to find whatchanges
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 executethem
> locally if you need to. > > --- > > On a related note, I am also working on the speed.python.org <http://speed.python.org> > <http://speed.python.org> server to provide more automation and > ideally some integrations with GitHub to detect performanceregressions. 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 candetect 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 workon trying to
> automatically comment or PRs or on bpo if > we detect that a commit has introduced some notable performanceregression.
> > Regards from sunny London, > Pablo Galindo Salgado. > > _______________________________________________ > python-committers mailing list -- python-committers@python.org <mailto:python-committers@python.org> > To unsubscribe send an email topython-committers-leave@python.org
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