[yt-dev] profiles on non-prgio sets

david collins antpuncher at gmail.com
Wed Mar 14 09:14:23 PDT 2012


> 512^3, bunch of subgrids, with 64 cores totalling 12 gb (i.e., just
> shy of 200mb / core) sounds okay to me.  I would guess you are

Ok, I've pulled together some more details.

If I run this 8 cores running a [Density,Density] profile (so, should
only have a single field) it fails claiming I'm using 31 Gb, which I
have a hard time understanding-- that's nearly 4 Gb per core.

I did the same analysis with a more recent (PRGIO) 512^3 with
thousands of grids (4 levels by 2) (many more than in the first set),
same job script, and it runs fine.

Anyhow, this isn't a huge deal, since non-prgio datasets are far from
the norm these days, and it works fine in serial.

Does cProfile work in parallel, and does it do memory work?

d.

> seriously disk limited for the analysis itself, but you can verify
> this by running:
>
> python2.7 -m cProfile -o ytprof.cprof my_script.py
>
> and then using either pyprof2html (requires Jinja2, sold separately)
> or the stats module to examine it.
>
> -Matt
>
> On Wed, Mar 14, 2012 at 11:15 AM, david collins <antpuncher at gmail.com> wrote:
>>> 64 cores, using 12GB on each?  That's a problem.  MassFraction it
>>
>> 12Gb total, but still...  I'll grab some more failure info and get
>> back to you.  In serial it ran fine, and took about 1 hour for both
>> [density,cellmass] and [density,cellvolume] within the default
>> head-node allowance on nautilus, which is 12Gb.  Timing wise longer
>> than I want to deal with, but it does run.
>>
>> d.
>>
>>> sounds like has a handful of dependencies -- CellMassMsun, which
>>> depends on Density and dx, but dx should be used as a single value not
>>> as a field.  So that gives 3*512^3*64 bits = 3 gigabytes, but that's a
>>> far cry from 12 gb/core.  Plus, the domain decomp for profiles is
>>> per-grid -- so only one of your cores should get assigned the root
>>> grid.  This is very bizarre.
>>>
>>>>
>>>> Would lazy_reader off change things?
>>>
>>> Yes, but it would make them worse.  :)
>>>
>>> -Matt
>>>
>>>>
>>>> Thanks,
>>>> d.
>>>>
>>>>> Are you running in parallel? Which fields are you profiling? Do they have
>>>>> lots of dependencies, or require ghost zones? Is yt using lazy_reader? Does
>>>>> your data have many grids?
>>>>
>>>>
>>>>>
>>>>> Matt
>>>>>
>>>>> On Mar 14, 2012 12:37 AM, "david collins" <antpuncher at gmail.com> wrote:
>>>>>>
>>>>>> I should add that this was done on 64 cores-- in serial it works fine,
>>>>>> just slow.
>>>>>>
>>>>>> On Tue, Mar 13, 2012 at 9:35 PM, david collins <antpuncher at gmail.com>
>>>>>> wrote:
>>>>>> > Hi, all--
>>>>>> >
>>>>>> > I have an old dataset that I'm trying to make profiles on.  It's a
>>>>>> > 512^3 root grid, but was written with ParallelRootGridIO off.  I find
>>>>>> > that it's using strange amounts of memory, more than 12 Gb.  Is this a
>>>>>> > known problem with a straight forward work-around?
>>>>>> >
>>>>>> > d.
>>>>>> >
>>>>>> > --
>>>>>> > Sent from my computer.
>>>>>>
>>>>>>
>>>>>>
>>>>>> --
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