[Swift-devel] ws-gram tests
Mihael Hategan
hategan at mcs.anl.gov
Fri Feb 8 16:12:43 CST 2008
Yep. Looks much better. How stable is this otherwise?
On Fri, 2008-02-08 at 15:02 -0600, Mihael Hategan wrote:
> On a first look it indeed looks like the gc is more successful at
> cleaning stuff up.
>
> On Fri, 2008-02-08 at 13:21 -0600, feller at mcs.anl.gov wrote:
> > Try the attached 4.0 compliant jar in your tests by dropping
> > it in your 4.0.x $GLOBUS_LOCATION/lib.
> > My tests showed about 2MB memory increase per 100 GramJob
> > objects which sounds to me like a reasonable number (about 20k
> > per GramJob object ignoring the notification consumer manager
> > in one job - if my calculations are right)
> >
> > Martin
> >
> > >
> > > On Fri, 2008-02-08 at 11:19 -0600, feller at mcs.anl.gov wrote:
> > >> Mihael,
> > >>
> > >> i think i found the memory hole in GramJob.
> > >> 100 jobs in a test of mine consumed about 23MB (constantly
> > >> growing) before the fix and 8MB (very slowly growing) after
> > >> the fix. The big part of that (7MB) is used right from the
> > >> first job which may be the NotificationConsumerManager.
> > >> Will commit that change soon to 4.0 branch and you may try
> > >> it then.
> > >> Are you using 4.0.x in your tests?
> > >
> > > Yes. If there are no API changes, you can send me the jar file. I don't
> > > have enough knowledge to selectively build WS-GRAM, nor enough disk
> > > space to build the whole GT.
> > >
> > >>
> > >> Martin
> > >>
> > >> >>> >
> > >> >>> > These are both hacks. I'm not sure I want to go there. 300K per
> > >> job
> > >> >>> is
> > >> >>> a
> > >> >>> > bit too much considering that swift (which has to consider many
> > >> more
> > >> >>> > things) has less than 10K overhead per job.
> > >> >>> >
> > >> >>>
> > >> >>>
> > >> >>> For my better understanding:
> > >> >>> Do you start up your own notification consumer manager that listens
> > >> for
> > >> >>> notifications of all jobs or do you let each GramJob instance listen
> > >> >>> for
> > >> >>> notifications itself?
> > >> >>> In case you listen for notifications yourself: do you store
> > >> >>> GramJob objects or just EPR's of jobs and create GramJob objects if
> > >> >>> needed?
> > >> >>
> > >> >> Excellent points. I let each GramJob instance listen for
> > >> notifications
> > >> >> itself. What I observed is that it uses only one container for that.
> > >> >>
> > >> >
> > >> > Shoot! i didn't know that and thought there would be a container per
> > >> > GramJob in that case. That's the core mysteries with notifications.
> > >> > Anyway: I did a quick check some days ago and found that GramJob is
> > >> > surprisingly greedy regarding memory as you said. I'll have to further
> > >> > check what it is, but will probably not do that before 4.2 is out.
> > >> >
> > >> >
> > >> >> Due to the above, a reference to the GramJob is kept anyway,
> > >> regardless
> > >> >> of whether that reference is in client code or the local container.
> > >> >>
> > >> >> I'll try to profile a run and see if I can spot where the problems
> > >> are.
> > >> >>
> > >> >>>
> > >> >>> Martin
> > >> >>>
> > >> >>> >>
> > >> >>> >> The core team will be looking at improving notifications once
> > >> their
> > >> >>> >> other 4.2 deliverables are done.
> > >> >>> >>
> > >> >>> >> -Stu
> > >> >>> >>
> > >> >>> >> Begin forwarded message:
> > >> >>> >>
> > >> >>> >> > From: feller at mcs.anl.gov
> > >> >>> >> > Date: February 1, 2008 9:41:05 AM CST
> > >> >>> >> > To: "Jaime Frey" <jfrey at cs.wisc.edu>
> > >> >>> >> > Cc: "Stuart Martin" <smartin at mcs.anl.gov>, "Terrence Martin"
> > >> >>> >> <tmartin at physics.ucsd.edu
> > >> >>> >> > >, "Martin Feller" <feller at mcs.anl.gov>, "charles bacon"
> > >> >>> >> <bacon at mcs.anl.gov
> > >> >>> >> > >, "Suchandra Thapa" <sthapa at ci.uchicago.edu>, "Rob Gardner"
> > >> >>> >> <rwg at hep.uchicago.edu
> > >> >>> >> > >, "Jeff Porter" <rjporter at lbl.gov>, "Alain Roy"
> > >> >>> <roy at cs.wisc.edu>,
> > >> >>> >> > "Todd Tannenbaum" <tannenba at cs.wisc.edu>, "Miron Livny"
> > >> >>> >> <miron at cs.wisc.edu
> > >> >>> >> > >
> > >> >>> >> > Subject: Re: Condor-G WS GRAM memory usage
> > >> >>> >> >
> > >> >>> >> >> On Jan 31, 2008, at 6:26 PM, Jaime Frey wrote:
> > >> >>> >> >>
> > >> >>> >> >>> On Jan 30, 2008, at 12:25 PM, Stuart Martin wrote:
> > >> >>> >> >>>
> > >> >>> >> >>>> On Jan 30, 2008, at Jan 30, 11:46 AM, Jaime Frey wrote:
> > >> >>> >> >>>>
> > >> >>> >> >>>>> Terrence Martin's scalability testing of Condor-G with WS
> > >> GRAM
> > >> >>> >> >>>>> raised some concerns about memory usage on the client side.
> > >> I
> > >> >>> did
> > >> >>> >> >>>>> some profiling of Condor-G's WS GRAM GAHP server, which
> > >> >>> appeared
> > >> >>> >> >>>>> to be the primary memory consumer. The GAHP server is a
> > >> >>> wrapper
> > >> >>> >> >>>>> around the java client libraries for WS GRAM.
> > >> >>> >> >>>>>
> > >> >>> >> >>>>> In my tests, I submitted variable numbers of jobs up to 30
> > >> at
> > >> >>> a
> > >> >>> >> >>>>> time. The jobs were 2-minute sleep jobs with minimal data
> > >> >>> >> >>>>> transfer. All of the jobs overlapped in submission and
> > >> >>> execution.
> > >> >>> >> >>>>> Here is what I've discovered so far.
> > >> >>> >> >>>>>
> > >> >>> >> >>>>> Aside from the heap available to the java code, the jvm
> > >> used
> > >> >>> 117
> > >> >>> >> >>>>> megs of non-shared memory and 74 megs of shared memory.
> > >> >>> Condor-G
> > >> >>> >> >>>>> creates one GAHP server for each (local uid, X509 DN) pair.
> > >> >>> >> >>>>>
> > >> >>> >> >>>>> The maximum jvm heap usage (as reported by the garbage
> > >> >>> collector)
> > >> >>> >> >>>>> was about 9 megs plus 0.9 megs per job. When the GAHP was
> > >> >>> >> >>>>> quiescent (jobs executing, Condor-G waiting for them to
> > >> >>> complete),
> > >> >>> >> >>>>> heap usage was about 5 megs plus 0.6 megs per job.
> > >> >>> >> >>>>>
> > >> >>> >> >>>>> The only long-term memory per job that I know of in the
> > >> GAHP
> > >> >>> is
> > >> >>> >> >>>>> for the notification sink for job status callbacks. 600kb
> > >> >>> seems
> > >> >>> a
> > >> >>> >> >>>>> little high for that. Stu, could someone on Globus help us
> > >> >>> >> >>>>> determine if we're using the notification sinks
> > >> inefficiently?
> > >> >>> >> >>>>
> > >> >>> >> >>>> Martin just looked and for the most part, there is nothing
> > >> >>> wrong
> > >> >>> >> >>>> with how condor-g manages the callback sink.
> > >> >>> >> >>>> However, one improvement that would reduce the memory used
> > >> per
> > >> >>> job
> > >> >>> >> >>>> would be to not have a notification consumer per job.
> > >> Instead
> > >> >>> use
> > >> >>> >> >>>> one for all jobs.
> > >> >>> >> >>>>
> > >> >>> >> >>>> Also, Martin recently did some analysis on condor-g stress
> > >> >>> tests
> > >> >>> >> >>>> and found that notifications are building up on the in the
> > >> >>> GRAM4
> > >> >>> >> >>>> service container and that is causing delays which seem to
> > >> be
> > >> >>> >> >>>> causing multiple problems. We're looking at this in a
> > >> separate
> > >> >>> >> >>>> effort with the GT Core team. But, after this was clear,
> > >> >>> Martin
> > >> >>> >> >>>> re-
> > >> >>> >> >>>> ran the condor-g test and relied on polling between condor-g
> > >> >>> and
> > >> >>> >> >>>> the GRAM4 service instead of notifications. Jaime, could
> > >> you
> > >> >>> >> >>>> repeat the no-notification test and see the difference in
> > >> >>> memory?
> > >> >>> >> >>>> The changes would be to increase the polling frequency in
> > >> >>> condor-g
> > >> >>> >> >>>> and comment out the subscribe for notification. You could
> > >> also
> > >> >>> >> >>>> comment out the notification listener call(s) too.
> > >> >>> >> >>>
> > >> >>> >> >>>
> > >> >>> >> >>> I did two new sets of tests today. The first used more
> > >> efficient
> > >> >>> >> >>> callback code in the GAHP (one notification consumer rather
> > >> than
> > >> >>> one
> > >> >>> >> >>> per job). The second disabled notifications and relied on
> > >> >>> polling
> > >> >>> >> >>> for job status changes.
> > >> >>> >> >>>
> > >> >>> >> >>> The more efficient callback code did not produce a noticeable
> > >> >>> >> >>> reduction in memory usage.
> > >> >>> >> >>>
> > >> >>> >> >>> Disabling notifications did reduce memory usage. The maximum
> > >> jvm
> > >> >>> >> >>> heap usage was roughly 8 megs plus 0.5 megs per job. The
> > >> minimum
> > >> >>> >> >>> heap usage after job submission and before job completion was
> > >> >>> about
> > >> >>> >> >>> 4 megs + 0.1 megs per job.
> > >> >>> >> >>
> > >> >>> >> >>
> > >> >>> >> >> I ran one more test with the improved callback code. This
> > >> time, I
> > >> >>> >> >> stopped storing the notification producer EPRs associated with
> > >> >>> the
> > >> >>> >> >> GRAM job resources. Memory usage went down markedly.
> > >> >>> >> >>
> > >> >>> >> >> I was told the client had to explicitly destroy these
> > >> serve-side
> > >> >>> >> >> notification producer resources when it destroys the job,
> > >> >>> otherwise
> > >> >>> >> >> they hang around bogging down the server. Is this still the
> > >> case?
> > >> >>> The
> > >> >>> >> >> server can't destroy notification producers when their sources
> > >> of
> > >> >>> >> >> information are destroyed?
> > >> >>> >> >>
> > >> >>> >> >
> > >> >>> >> > This reminds me of the odd fact that i had to suddenly grant
> > >> much
> > >> >>> more
> > >> >>> >> > memory to Condor-g as soon as condor-g started storing EPRs of
> > >> >>> >> > subscription resources to be able to destroy them eventually.
> > >> >>> >> > Those EPR's are maybe not so tiny as they look like.
> > >> >>> >> >
> > >> >>> >> > For 4.0: yes, currently you'll have to store and eventually
> > >> >>> destroy
> > >> >>> >> > subscription resources manually to avoid heaping up persistence
> > >> >>> data
> > >> >>> >> > on the server-side.
> > >> >>> >> > For 4.2: no, you won't have to store them. A job resource will
> > >> >>> >> > destroy all subscription resources when it's destroyed.
> > >> >>> >> >
> > >> >>> >> > Overall i suggest to concentrate on 4.2 gram since the
> > >> "container
> > >> >>> >> > hangs in job destruction" problem won't exist anymore.
> > >> >>> >> >
> > >> >>> >> > Sorry, Jaime, i still can't provide you with 100% reliable 4.2
> > >> >>> changes
> > >> >>> >> > in Gram in 4.2. I'll do so as soon as i can. I wonder if it
> > >> makes
> > >> >>> >> > sense
> > >> >>> >> > for us to do the 4.2-related changes in Gahp and hand it to you
> > >> >>> for
> > >> >>> >> > fine-tuning then?
> > >> >>> >> >
> > >> >>> >> > Martin
> > >> >>> >>
> > >> >>> >>
> > >> >>> >>
> > >> >>> >>
> > >> >>> >> On Feb 8, 2008, at Feb 8, 9:19 AM, Ian Foster wrote:
> > >> >>> >>
> > >> >>> >> > Mihael:
> > >> >>> >> >
> > >> >>> >> > That's great, thanks!
> > >> >>> >> >
> > >> >>> >> > Ian.
> > >> >>> >> >
> > >> >>> >> > Mihael Hategan wrote:
> > >> >>> >> >> I did a 1024 job run today with ws-gram.
> > >> >>> >> >> I painted the results here:
> > >> >>> >> >> http://www-unix.mcs.anl.gov/~hategan/s/g.html
> > >> >>> >> >>
> > >> >>> >> >> Seems like client memory per job is about 370k. Which is quite
> > >> a
> > >> >>> lot.
> > >> >>> >> >> What kinda worries me is that it doesn't seem to go down after
> > >> >>> the
> > >> >>> >> >> jobs
> > >> >>> >> >> are done, so maybe there's a memory leak, or maybe the garbage
> > >> >>> >> >> collector
> > >> >>> >> >> doesn't do any major collections. I'll need to profile this to
> > >> >>> see
> > >> >>> >> >> exactly what we're talking about.
> > >> >>> >> >>
> > >> >>> >> >> The container memory is figured by looking at the process in
> > >> >>> /proc.
> > >> >>> >> >> It's
> > >> >>> >> >> total memory including shared libraries and things. But
> > >> libraries
> > >> >>> >> >> take a
> > >> >>> >> >> fixed amount of space, so a fuzzy correlation can probably be
> > >> >>> made.
> > >> >>> >> >> It
> > >> >>> >> >> looks quite similar to the amount of memory eaten on the
> > >> client
> > >> >>> side
> > >> >>> >> >> (per job).
> > >> >>> >> >>
> > >> >>> >> >> CPU-load-wise, WS-GRAM behaves. There is some work during the
> > >> >>> time
> > >> >>> >> >> the
> > >> >>> >> >> jobs are submitted, but the machine itself seems responsive. I
> > >> >>> have
> > >> >>> >> >> yet
> > >> >>> >> >> to plot the exact submission time for each job.
> > >> >>> >> >>
> > >> >>> >> >> So at this point I would recommend trying ws-gram as long as
> > >> >>> there
> > >> >>> >> >> aren't too many jobs involved (i.e. under 4000 parallel jobs),
> > >> >>> and
> > >> >>> >> >> while
> > >> >>> >> >> making sure the jvm has enough heap. More than that seems like
> > >> a
> > >> >>> >> >> gamble.
> > >> >>> >> >>
> > >> >>> >> >> Mihael
> > >> >>> >> >>
> > >> >>> >> >> _______________________________________________
> > >> >>> >> >> Swift-devel mailing list
> > >> >>> >> >> Swift-devel at ci.uchicago.edu
> > >> >>> >> >> http://mail.ci.uchicago.edu/mailman/listinfo/swift-devel
> > >> >>> >> >>
> > >> >>> >> >>
> > >> >>> >> >
> > >> >>> >>
> > >> >>> >
> > >> >>> >
> > >> >>>
> > >> >>>
> > >> >>
> > >> >>
> > >> >
> > >> >
> > >> >
> > >>
> > >>
> > >
> > >
>
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