[yt-users] How to efficiently control the memory in yt with large simulation?

[Geoffrey So]

I believe you can access rectangular sub volume of the data with something
like

sv = pf.h.region([0.5]*3, [0.21, .21, .72], [.28, .28, .79])

Shown here when running halo finder on a sub volume
http://yt-project.org/docs/2.6/analyzing/analysis_modules/running_halofinder.html?highlight=sub%20region

And you can use other 3D objects like spheres, ellipsoids etc, for a
thin slice of the data you can make your rectangular region small in
one of the dimension.

When making plots just pass in the sv 3D sub volume object instead of
the usual pf for plotting the entire simulation.

Hope that helps.


From

G.S.




On Fri, Dec 6, 2013 at 8:41 AM, Junhwan Choi (최준환)
<choi.junhwan at gmail.com>wrote:

> Thank you Matt and Romain,
>
> Now, I understand it is a more fundamental issue in the yt with
> Ramses, and I need to wait yt to be updated.
> Meanwhile, is there any way I can access small fraction of the
> simulation data (such as thin slice of the data) and make some
> visualization plots such as thin projection and slice?
> If so, I can reduce the required memory.
> Is it possible?
>
> Thank you,
> Junhwan
>
>
> On Fri, Dec 6, 2013 at 8:56 AM, Matthew Turk <matthewturk at gmail.com>
> wrote:
> > On Fri, Dec 6, 2013 at 9:54 AM, Romain Teyssier
> > <romain.teyssier at gmail.com> wrote:
> >> One possibility would be to define a bounding box that yt uses to upload
> >> ramses data only when contained in this bounding box.
> >> This can be done efficiently using the Hilbert key.
> >>
> >> Romain
> >
> > That would be good, and we could probably port the code Doug Rudd
> > wrote to use SFC logic for detecting which zones to parse over to
> > RAMSES, as well.
> >
> > Today is out for me on this, because of other things, but with this I
> > think we might be able to make it work in the near future, like
> > mid-next week, assuming all goes well otherwise.
> >
> > -Matt
> >
> >>
> >> On 06 Dec 2013, at 15:49, Matthew Turk <matthewturk at gmail.com> wrote:
> >>
> >> Hi Junhwan,
> >>
> >> There's some more background on this issue here:
> >>
> >>
> http://lists.spacepope.org/pipermail/yt-users-spacepope.org/2013-November/004265.html
> >>
> >> Basically, what it amounts to is:
> >>
> >> * Right now RAMSES uses too much memory and duplicates the full mesh
> >> on every processor
> >> * This is not how it will always be
> >> * Unfortunately changing this can't be prioritized in the next couple
> weeks
> >>
> >> Your mesh is *particularly* large for what we've dealt with before.
> >> As it stands, I would be surprised if it will work.  The fix for this
> >> would be to change the Octrees to only parse on demand rather than at
> >> instantiation of the RAMSESHierarchy.  Sam Geen and I have talked a
> >> bit about this, and he may be interested in working on it.  It's a
> >> change that also will happen for N-body datasets (differently) and
> >> it's definitely planned to come, but it isn't being prioritized at
> >> this very moment because of other pressing concerns.
> >>
> >> On Thu, Dec 5, 2013 at 10:47 PM, Junhwan Choi (최준환)
> >> <choi.junhwan at gmail.com> wrote:
> >>
> >> Hi all,
> >>
> >> I try to make some visualizations (density/temperature project) for
> >> large simulation with yt.
> >> The simulation is 4096^3 unigrid Ramses simulation.
> >>
> >> I try to implement the basics density and temperature projection plot
> >> with following script and I got memory problem and yt run is crashed.
> >> =====
> >> from yt.mods import *
> >>
> >> ds = load("../output_00048/info_00048.txt", fields =
> >> ["Density","x-velocity",
> >> "y-velocity","z-velocity","Pressure","Metallicity","Rad"])
> >> center = [0., 0., 0.]
> >>
> >> pw = ProjectionPlot(ds, "x", ("gas", "Density"),
> >> weight_field="Density", center=center)
> >> pw.zoom(1.01)
> >> pw.save("allviewGas")
> >> pw = ProjectionPlot(ds, "y", ("gas", "Density"),
> >> weight_field="Density", center=center)
> >> pw.zoom(1.01)
> >> pw.save("allviewGas")
> >> pw = ProjectionPlot(ds, "z", ("gas", "Density") ,
> >> weight_field="Density", center=center)
> >> pw.zoom(1.01)
> >> pw.save("allviewGas")
> >>
> >> pw = ProjectionPlot(ds, "x", "Temperature", weight_field="Density",
> >> center=center)
> >> pw.zoom(1.01)
> >> pw.save("allviewGas")
> >> pw = ProjectionPlot(ds, "y", "Temperature", weight_field="Density",
> >> center=center)
> >> pw.zoom(1.01)
> >> pw.save("allviewGas")
> >> pw = ProjectionPlot(ds, "z", "Temperature" , weight_field="Density",
> >> center=center)
> >> pw.zoom(1.01)
> >> pw.save("allviewGas")
> >> ====
> >>
> >> Is there any way to reduce the memory usage when I make visualization?
> >> If I use slice instead of projection, can I save the memory?
> >> I saw there is parallelization for yt. Does parallelization distribute
> >> the data at the beginning of the read?
> >> (But, I prefer to do so w/o parallelization at this moment.)
> >>
> >>
> >> In principle, yes, slices will considerably reduce the memory, modulo
> >> the overhead from having all your octrees in memory at once -- which
> >> will be considerable.
> >>
> >> I will spend some time thinking if there's a hotfix we can apply to
> >> make this work for you right now, as is, but I suspect it may be a
> >> little time until it can be properly implemented.
> >>
> >> -Matt
> >>
> >>
> >> Thank you in advance,
> >> Junhwan
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