[yt-users] Volume Rendering and Memory usage

Matthew Turk matthewturk at gmail.com
Wed Feb 2 09:55:50 PST 2011 

Hi Andrew,

This is I think a spurious issue -- it comes from the calculation of
the radius when detecting which derived fields can be used by yt.  I
would actually guess that you see this whenever the hierarchy is
instantiated:

pf.h

and not only when the PlotCollection goes out.  I tried kind of hard
to eliminate this issue but I couldn't figure out a way; I think it's
cosmetic and unrelated, though.  Can you have a go at the checking for
NaNs code?

-Matt

On Wed, Feb 2, 2011 at 12:51 PM, Andrew Myers <atmyers at berkeley.edu> wrote:
> Actually, and I probably should have mentioned this earlier, but I remember
> now that once I upgraded to yt-2.0 I started seeing warning messages like:
>
> Warning: invalid value encountered in sqrt
>
> when I create a plot collection from this dataset, which supports the
> negative value theory.  I assume that these values were always there, but
> yt-2.0 started warning me about them. Probably the center of the domain does
> not include the bad value(s), so it only chokes the volume renderer if I
> make the domain large enough. Thanks for the help, both of you!
>
> ~Andrew
>
> On Wed, Feb 2, 2011 at 9:42 AM, Matthew Turk <matthewturk at gmail.com> wrote:
>>
>> Jeff, you are absolutely right.  Maybe a better solution would be:
>>
>> for g in pf.h.grids:
>>   if na.any(na.isnan.na.log10(grid["Density"]))): raise RuntimeError
>>
>> That should be a more true-to-life method.
>>
>> -Matt
>>
>> On Wed, Feb 2, 2011 at 12:40 PM, j s oishi <jsoishi at gmail.com> wrote:
>> > Hi Matt,
>> >
>> > Could it not also be from a negative value that has had its log() taken?
>> >
>> > j
>> >
>> >
>> >
>> >
>> >
>> > On Wed, Feb 2, 2011 at 9:38 AM, Matthew Turk <matthewturk at gmail.com>
>> > wrote:
>> >> Hi Andrew,
>> >>
>> >> Okay, I have seen this before.  I think it is related to a bad data
>> >> value that it's trying to traverse.  In the past this has been caused
>> >> by NaNs, usually from a zero value that has been logged, as I believe
>> >> other values should be handled correctly.  Can you try this code for
>> >> me?
>> >>
>> >> for g in pf.h.grids:
>> >>    if na.any(grid["Density"] == 0): raise RuntimeError
>> >>
>> >> and see if it proceeds to completion?  I will see if I can think of a
>> >> good way to handle NaNs; obviously a segfault is a pretty poor
>> >> strategy.
>> >>
>> >> -Matt
>> >>
>> >> On Wed, Feb 2, 2011 at 12:32 PM, Andrew Myers <atmyers at berkeley.edu>
>> >> wrote:
>> >>> Hi Matt,
>> >>>
>> >>> Thanks for the help. This is the outcome of the "bt" command in gdb:
>> >>>
>> >>> (gdb) bt
>> >>> #0  __pyx_f_2yt_9utilities_9amr_utils_FIT_get_value
>> >>> (__pyx_v_self=0x87ab9c0,
>> >>> __pyx_v_dt=0.00024472523295100413, __pyx_v_dvs=0x50e9d670,
>> >>> __pyx_v_rgba=0x7fffd8a94f60,
>> >>>     __pyx_v_grad=<value optimized out>) at
>> >>> yt/utilities/amr_utils.c:13705
>> >>> #1
>> >>> __pyx_f_2yt_9utilities_9amr_utils_21TransferFunctionProxy_eval_transfer
>> >>> (__pyx_v_self=0x87ab9c0, __pyx_v_dt=0.00024472523295100413,
>> >>> __pyx_v_dvs=0x50e9d670,
>> >>>     __pyx_v_rgba=0x7fffd8a94f60, __pyx_v_grad=<value optimized out>)
>> >>> at
>> >>> yt/utilities/amr_utils.c:14285
>> >>> #2  0x00002b5e0a62c464 in
>> >>> __pyx_f_2yt_9utilities_9amr_utils_15PartitionedGrid_sample_values
>> >>> (__pyx_v_self=0x50e9d610, __pyx_v_v_pos=<value optimized out>,
>> >>>     __pyx_v_v_dir=<value optimized out>,
>> >>> __pyx_v_enter_t=23.346866210722702,
>> >>> __pyx_v_exit_t=<value optimized out>, __pyx_v_ci=<value optimized
>> >>> out>,
>> >>>     __pyx_v_rgba=0x7fffd8a94f60, __pyx_v_tf=0x87ab9c0) at
>> >>> yt/utilities/amr_utils.c:17719
>> >>> #3  0x00002b5e0a62ce16 in
>> >>> __pyx_f_2yt_9utilities_9amr_utils_15PartitionedGrid_integrate_ray
>> >>> (__pyx_v_self=0x50e9d610, __pyx_v_v_pos=0x7fffd8a94fd0,
>> >>>     __pyx_v_v_dir=0x45457d0, __pyx_v_rgba=0x7fffd8a94f60,
>> >>> __pyx_v_tf=0x87ab9c0) at yt/utilities/amr_utils.c:17386
>> >>> #4  0x00002b5e0a624876 in
>> >>> __pyx_pf_2yt_9utilities_9amr_utils_15PartitionedGrid_2cast_plane
>> >>> (__pyx_v_self=0x50e9d610, __pyx_args=<value optimized out>,
>> >>>     __pyx_kwds=<value optimized out>) at
>> >>> yt/utilities/amr_utils.c:16199
>> >>> #5  0x0000000000495124 in call_function (f=0x5a7ce490,
>> >>> throwflag=<value
>> >>> optimized out>) at Python/ceval.c:3706
>> >>> #6  PyEval_EvalFrameEx (f=0x5a7ce490, throwflag=<value optimized out>)
>> >>> at
>> >>> Python/ceval.c:2389
>> >>> #7  0x00000000004943ff in call_function (f=0x87aa260, throwflag=<value
>> >>> optimized out>) at Python/ceval.c:3792
>> >>> #8  PyEval_EvalFrameEx (f=0x87aa260, throwflag=<value optimized out>)
>> >>> at
>> >>> Python/ceval.c:2389
>> >>> #9  0x0000000000495d6d in PyEval_EvalCodeEx (co=0x24286c0,
>> >>> globals=<value
>> >>> optimized out>, locals=<value optimized out>, args=0xb62c38,
>> >>> argcount=2,
>> >>> kws=0xb62c48,
>> >>>     kwcount=0, defs=0x242a2a8, defcount=1, closure=0x0) at
>> >>> Python/ceval.c:2968
>> >>> #10 0x0000000000493c79 in call_function (f=0xb62ac0, throwflag=<value
>> >>> optimized out>) at Python/ceval.c:3802
>> >>> #11 PyEval_EvalFrameEx (f=0xb62ac0, throwflag=<value optimized out>)
>> >>> at
>> >>> Python/ceval.c:2389
>> >>> #12 0x0000000000495d6d in PyEval_EvalCodeEx (co=0x2b5e01aed288,
>> >>> globals=<value optimized out>, locals=<value optimized out>, args=0x0,
>> >>> argcount=0, kws=0x0, kwcount=0,
>> >>>     defs=0x0, defcount=0, closure=0x0) at Python/ceval.c:2968
>> >>> #13 0x0000000000495db2 in PyEval_EvalCode (co=0x87ab9c0,
>> >>> globals=0x50e9d670,
>> >>> locals=0x72f1270) at Python/ceval.c:522
>> >>> #14 0x00000000004b7ee1 in run_mod (fp=0xb54ed0,
>> >>> filename=0x7fffd8a965a4
>> >>> "vr.py", start=<value optimized out>, globals=0xb03190,
>> >>> locals=0xb03190,
>> >>> closeit=1,
>> >>>     flags=0x7fffd8a958d0) at Python/pythonrun.c:1335
>> >>> #15 PyRun_FileExFlags (fp=0xb54ed0, filename=0x7fffd8a965a4 "vr.py",
>> >>> start=<value optimized out>, globals=0xb03190, locals=0xb03190,
>> >>> closeit=1,
>> >>> flags=0x7fffd8a958d0)
>> >>>     at Python/pythonrun.c:1321
>> >>> #16 0x00000000004b8198 in PyRun_SimpleFileExFlags (fp=<value optimized
>> >>> out>,
>> >>> filename=0x7fffd8a965a4 "vr.py", closeit=1, flags=0x7fffd8a958d0) at
>> >>> Python/pythonrun.c:931
>> >>> #17 0x0000000000413e4f in Py_Main (argc=<value optimized out>,
>> >>> argv=0x7fffd8a959f8) at Modules/main.c:599
>> >>> #18 0x00002b5e0259a994 in __libc_start_main () from /lib64/libc.so.6
>> >>> #19 0x00000000004130b9 in _start ()
>> >>>
>> >>> Thanks,
>> >>> Andrew
>> >>>
>> >>>
>> >>> On Wed, Feb 2, 2011 at 5:25 AM, Matthew Turk <matthewturk at gmail.com>
>> >>> wrote:
>> >>>>
>> >>>> Hi Andrew,
>> >>>>
>> >>>> That's an odd bug!  Do you think you could get a backtrace from the
>> >>>> segfault?  You might do this by setting your core dump ulimit to
>> >>>> unlimited:
>> >>>>
>> >>>> [in base]
>> >>>>
>> >>>> ulimit -c unlimited
>> >>>>
>> >>>> [in csh]
>> >>>>
>> >>>> limit coredumpsize unlimited
>> >>>>
>> >>>> and then running again.  When the core dump gets spit out,
>> >>>>
>> >>>> gdb python2.6 -c that_core_file
>> >>>> bt
>> >>>>
>> >>>> should tell us where in the code it died.  Sam Skillman should have a
>> >>>> better idea about any possible memory issues, but the segfault to me
>> >>>> feels like maybe there's a roundoff that's putting it outside a grid
>> >>>> data array space or something.
>> >>>>
>> >>>> Sorry for the trouble,
>> >>>>
>> >>>> Matt
>> >>>>
>> >>>> On Tue, Feb 1, 2011 at 11:13 PM, Andrew Myers <atmyers at berkeley.edu>
>> >>>> wrote:
>> >>>> > Hello yt users,
>> >>>> >
>> >>>> > I'm trying to volume render an Orion simulation with about 6,000
>> >>>> > grids
>> >>>> > and
>> >>>> > 100 million cells, and I think I'm running out of memory. I don't
>> >>>> > know
>> >>>> > if
>> >>>> > this is large compared to other simulations people have volume
>> >>>> > rendered
>> >>>> > before, but if I set the width of my field of view to be 0.02 pc
>> >>>> > (20
>> >>>> > times
>> >>>> > smaller than the entire domain), the following code works fine. If
>> >>>> > I set
>> >>>> > it
>> >>>> > to 0.04 pc or anything larger, the code segfaults, which I assume
>> >>>> > means
>> >>>> > I'm
>> >>>> > running out of memory. This happens no matter how many cores I run
>> >>>> > on -
>> >>>> > running in parallel seems to be speed up the calculation, but not
>> >>>> > increase
>> >>>> > the size of the domain I can render. Am I doing something wrong? Or
>> >>>> > do I
>> >>>> > just need to find a machine with more memory to do this on? The one
>> >>>> > I'm
>> >>>> > using now has 3 gigs per core, which strikes me as pretty solid.
>> >>>> > I'm
>> >>>> > using
>> >>>> > the trunk version of yt-2.0. Here's the script for reference:
>> >>>> >
>> >>>> > from yt.mods import *
>> >>>> >
>> >>>> > pf = load("plt01120")
>> >>>> >
>> >>>> > dd = pf.h.all_data()
>> >>>> > mi, ma = na.log10(dd.quantities["Extrema"]("Density")[0])
>> >>>> > mi -= 0.1 ; ma += 0.1 # To allow a bit of room at the
>> >>>> > edges
>> >>>> >
>> >>>> > tf = ColorTransferFunction((mi, ma))
>> >>>> > tf.add_layers(8, w=0.01)
>> >>>> > c = na.array([0.0,0.0,0.0])
>> >>>> > L = na.array([1.0, 1.0, 1.0])
>> >>>> > W = 6.17e+16 # 0.02
>> >>>> > pc
>> >>>> >
>> >>>> > N = 512
>> >>>> >
>> >>>> > cam = Camera(c, L, W, (N,N), tf, pf=pf)
>> >>>> > fn = "%s_image.png" % pf
>> >>>> >
>> >>>> > cam.snapshot(fn)
>> >>>> >
>> >>>> > Thanks,
>> >>>> > Andrew Myers
>> >>>> >
>> >>>> >
>> >>>> >
>> >>>> > _______________________________________________
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>> >>>> >
>> >>>> >
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