[Swift-devel] ws-gram tests

Fri Feb 8 13:21:29 CST 2008

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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