[Swift-devel] ws-gram tests

[feller at mcs.anl.gov]

I can't see any stability issues here. The only thing i changed
is using

EndpointReferenceType jobEPR = (EndpointReferenceType)
    ObjectSerializer.clone(response.getManagedJobEndpoint());

instead of

EndpointReferenceType jobEPR = response.getManagedJobEndpoint();

at 2 or 3 locations in the code.

Rachana uses cloning in core too. So it's supposed to be
a stable thing.

A question though: Do you see a speedup in submission?

Martin


> 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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>
>