Floating point error with MPS Simulator. During contract_decompose function call. #147

sunggonkim · 2024-07-27T23:00:22Z

sunggonkim
Jul 27, 2024

Please refer to the end of discussion in this link (#109 (reply in thread)).
To summarize, I am having a floating point error following mps_algorithms.ipynb on Perlmutter at berkeley lab.

As for the latest request, @yangcal, Permutter has NVIDIA A100 GPUs.

As for the script, the code executes withtout an error.
Does this mean that I have to save the circuit after contract_decompose and load the circuit again before contract_decompose?

Answered by yangcal

Aug 6, 2024

I assume that nvidia 22.2 refers to the 22.2 SDK which contains the entire toolkit but only for CUDA 11. Perhaps that module is somehow interfering with the cuda12.5 that you got from conda installation of cuquantum-python. In any case, I'm glad that it's resolved.

View full answer

yangcal · 2024-07-28T01:08:34Z

yangcal
Jul 28, 2024
Maintainer

Thanks for sharing your finding, which seems to be a very tricky case. Can you run the entire notebook with environment variable CUTENSORNET_LOG_LEVEL=5 and share the last ~30 lines of the logging? Alternatively, it would also be very helpful if you could insert some print lines inside this code block to help us identify which line is causing the issues.

And one more question, is your installation of cuquantum-python based on pip, conda or our appliance container?

7 replies

sunggonkim Jul 29, 2024
Author

Thanks for the help.

removing abs_cutoff actually resolved the issue. We tried various svd_method which also spawned same error.
here is the list.
pip list
piplist.txt

LD_LIBRARY_PATH

/global/common/software/nersc/pm-2022q4/sw/evp-patch/lib64:/usr/local/cuda-12.2/compat:/opt/nvidia/hpc_sdk/Linux_x86_64/23.9/math_libs/12.2/lib64:/opt/nvidia/hpc_sdk/Linux_x86_64/23.9/cuda/12.2/extras/CUPTI/lib64:/opt/nvidia/hpc_sdk/Linux_x86_64/23.9/cuda/12.2/extras/Debugger/lib64:/opt/nvidia/hpc_sdk/Linux_x86_64/23.9/cuda/12.2/nvvm/lib64:/opt/nvidia/hpc_sdk/Linux_x86_64/23.9/cuda/12.2/lib64:/opt/nvidia/hpc_sdk/Linux_x86_64/23.9/math_libs/lib64:/opt/nvidia/hpc_sdk/Linux_x86_64/23.9/compilers/lib:/opt/cray/pe/papi/7.0.1.2/lib64:/opt/cray/libfabric/1.15.2.0/lib64

We are actually running this on conda environment with pip install. So it does spwan identical error
I think we identified the problem here.
When running test_tensor.py, we are getting identical error.

test_tensor.py::TestDecompose::test_svd[False-True-decompose_expr0-numpy-float32-C-None] Fatal
 Python error: Floating point exception

Also, here is the full output.
test_tensor_experimental.txt
test_tensor.txt

yangcal Jul 29, 2024
Maintainer

Your feedback is very informative. We will look into this and keep you posted for updates.

yangcal Jul 31, 2024
Maintainer

To follow up on this thread, can you generate a core dump on your end? Some reference here. Due to potential ABI compatibility issue, we may not be able to load the core file even if you share, nevertheless, you may see the traceback via gdb -c <core_dump_filename> python and share with us what you find there.

sunggonkim Jul 31, 2024
Author

According to the reference, It seems like we need sudo privilege to get core dump. However, unfortunately, we do not have sudo privilege in the system. Is there any way to get core dump without root privilege...?

yangcal Aug 1, 2024
Maintainer

I don't think sudo access is strictly needed to generate or debug a core dump file though this could potentially differ depending on your system. ulimit -c unlimited should enable core dumps for your session and core dumps are usually generated in the current working directory unless it has been modified by system-wide setting. Can you check if core dump can be located under the working directory? If not, Permutter system admin should know how to enable/redirect that as it's commonly used in debugging.

sunggonkim · 2024-08-02T00:58:16Z

sunggonkim
Aug 2, 2024
Author

Sorry about the confusion.
It was very weird permission-ish error from the perlmutter.

As file is too big, here is the onedrive link (Of my school) to the coredump file.
If you are not comfortable with external link, please let me know how to share the file in your preferred method!
Thanks

https://o365seoultech-my.sharepoint.com/:u:/g/personal/suggonkim_office_seoultech_ac_kr/EbRHhuwuQylKhuT9pFusUNQB4hC_8uYSAaAZuuHXyzdyEA?e=zKN9qa

1 reply

yangcal Aug 2, 2024
Maintainer

Due to ABI compatibility issue (my python executable does not match what you're using), I'm not able to debug based on your core dump file. Can you try the following steps in your environment?

First, start gdb with the core dump file using the following command:

gdb $(which python) core_dump_file

Then get a backtrace within gdb:

(gdb) bt

You should be able to see the backtrace from running these

sunggonkim · 2024-08-03T00:03:46Z

sunggonkim
Aug 3, 2024
Author

Here is the output from backtrace.

#0  0x00007fca25c4ba17 in ?? () from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcublas.so.12
#1  0x00007fca25d4d447 in ?? () from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcublas.so.12
#2  0x00007fca25d4deb4 in ?? () from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcublas.so.12
#3  0x00007fca25afe459 in cublasDdot_v2 () from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcublas.so.12
#4  0x00007fca61142b62 in ?? () from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcutensornet.so.2
#5  0x00007fca611289fa in ?? () from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcutensornet.so.2
#6  0x00007fca6115d26d in ?? () from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcutensornet.so.2
#7  0x00007fca611615c5 in cutensornetGateSplit ()
   from /global/homes/s/sgkim/.conda/envs/Tatis/lib/libcutensornet.so.2
#8  0x00007fcbf31c3cb8 in __pyx_f_9cuquantum_11cutensornet_9_internal_11cutensornet__cutensornetGateSplit(void*, void*, void const*, void*, void const*, void*, void const*, void*, void*, void*, void*, void*, cutensornetGateSplitAlgo_t, void*, cutensornetComputeType_t, void*, void*, CUstream_st*) ()
   from /pscratch/sd/s/sgkim/skim_cuquantum/cuQuantum-24.03.0/python/cuquantum/cutensornet/_internal/cutensornet.cpython-39-x86_64-linux-gnu.so
#9  0x00007fcbf31e7f6c in __pyx_f_9cuquantum_11cutensornet_13cycutensornet_cutensornetGateSplit(void*, void*, void const*, void*, void const*, void*, void const*, void*, void*, void*, void*, void*, cutensornetGateSplitAlgo_t, void*, cutensornetComputeType_t, void*, void*, CUstream_st*) ()
   from /pscratch/sd/s/sgkim/skim_cuquantum/cuQuantum-24.03.0/python/cuquantum/cutensornet/cycutensornet.cpython-39-x86_64-linux-gnu.so
#10 0x00007fcbf321f67a in __pyx_f_9cuquantum_11cutensornet_11cutensornet_gate_split(long, long, long, long, long, long, long, long, long, long, long, long, int, long, int, long, long, long, int) ()
   from /pscratch/sd/s/sgkim/skim_cuquantum/cuQuantum-24.03.0/python/cuquantum/cutensornet/cutensornet.cpython-39-x86_64-linux-gnu.so
#11 0x00007fcbf323047b in __pyx_pw_9cuquantum_11cutensornet_11cutensornet_109gate_split(_object*, _object*, _object*) ()
   from /pscratch/sd/s/sgkim/skim_cuquantum/cuQuantum-24.03.0/python/cuquantum/cutensornet/cutensornet.cpython-39-x86_64-linux-gnu.so
#12 0x00005602e486a6b6 in cfunction_call (func=0x7fcbf337a4f0, args=<optimized out>, kwargs=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Objects/methodobject.c:543
#13 0x00005602e48537ac in _PyObject_MakeTpCall (tstate=0x5602e4acc8b0, callable=0x7fcbf337a4f0, 
    args=<optimized out>, nargs=<optimized out>, keywords=0x0)
    at /usr/local/src/conda/python-3.9.19/Objects/call.c:191
#14 0x00005602e484ff10 in _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimized out>, args=<optimized out>, 
    callable=0x7fcbf337a4f0, tstate=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Include/cpython/abstract.h:116
#15 _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimized out>, args=0x5602f64fa3e8, 
callable=0x7fcbf337a4f0, tstate=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Include/cpython/abstract.h:103
#16 PyObject_Vectorcall (kwnames=0x0, nargsf=<optimized out>, args=0x5602f64fa3e8, callable=0x7fcbf337a4f0)
    at /usr/local/src/conda/python-3.9.19/Include/cpython/abstract.h:127
#17 call_function (kwnames=0x0, oparg=<optimized out>, pp_stack=<synthetic pointer>, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:5077
#18 _PyEval_EvalFrameDefault (tstate=<optimized out>, f=0x5602f64fa130, throwflag=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:3489
#19 0x00005602e484a184 in _PyEval_EvalFrame (throwflag=0, f=0x5602f64fa130, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Include/internal/pycore_ceval.h:40
#20 _PyEval_EvalCode (tstate=0x5602e4acc8b0, _co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kwnames=0x0, kwargs=0x5602e81f9398, 
    kwcount=0, kwstep=1, defs=0x0, defcount=<optimized out>, kwdefs=0x0, closure=0x0, name=0x7fcbc881ff30, 
    qualname=0x7fcbc881ff30) at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4329
#21 0x00005602e485b559 in _PyFunction_Vectorcall (func=<optimized out>, stack=<optimized out>, 
    nargsf=<optimized out>, kwnames=<optimized out>) at /usr/local/src/conda/python-3.9.19/Objects/call.c:396
#22 0x00005602e484b352 in _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimized out>, args=0x5602e81f9350, 
    callable=0x7fcbc888fb80, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Include/cpython/abstract.h:118
#23 PyObject_Vectorcall (kwnames=0x0, nargsf=<optimized out>, args=0x5602e81f9350, callable=0x7fcbc888fb80)
    at /usr/local/src/conda/python-3.9.19/Include/cpython/abstract.h:127
#24 call_function (kwnames=0x0, oparg=<optimized out>, pp_stack=<synthetic pointer>, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:5077
#25 _PyEval_EvalFrameDefault (tstate=<optimized out>, f=0x5602e81f90c0, throwflag=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:3520
#26 0x00005602e484a184 in _PyEval_EvalFrame (throwflag=0, f=0x5602e81f90c0, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Include/internal/pycore_ceval.h:40
#27 _PyEval_EvalCode (tstate=0x5602e4acc8b0, _co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kwnames=0x7fcbc5e32098, 
    kwargs=0x7fcbd9fab418, kwcount=2, kwstep=1, defs=0x0, defcount=<optimized out>, kwdefs=0x7fcbc8829300, 
    closure=0x0, name=0x7fcbf7019580, qualname=0x7fcbf7019580)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4329
#28 0x00005602e485b559 in _PyFunction_Vectorcall (func=<optimized out>, stack=<optimized out>, 
    nargsf=<optimized out>, kwnames=<optimized out>) at /usr/local/src/conda/python-3.9.19/Objects/call.c:396
#29 0x00005602e486917c in PyVectorcall_Call (kwargs=<optimized out>, tuple=<optimized out>, 
    callable=0x7fcbc88244c0) at /usr/local/src/conda/python-3.9.19/Objects/call.c:243
#30 _PyObject_Call (kwargs=<optimized out>, args=<optimized out>, callable=0x7fcbc88244c0, 
    tstate=<optimized out>) at /usr/local/src/conda/python-3.9.19/Objects/call.c:266
#31 PyObject_Call (callable=0x7fcbc88244c0, args=<optimized out>, kwargs=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Objects/call.c:293
#32 0x00005602e484f516 in do_call_core (kwdict=0x7fcbc5e35180, callargs=0x7fcbc5e7c180, func=0x7fcbc88244c0, 
    tstate=<optimized out>) at /usr/local/src/conda/python-3.9.19/Python/ceval.c:5125
#33 _PyEval_EvalFrameDefault (tstate=<optimized out>, f=0x5602f64ed350, throwflag=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:3582
#34 0x00005602e484a184 in _PyEval_EvalFrame (throwflag=0, f=0x5602f64ed350, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Include/internal/pycore_ceval.h:40
#35 _PyEval_EvalCode (tstate=0x5602e4acc8b0, _co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kwnames=0x7fcbf6d6edd8, 
    kwargs=0x5602e4b2ebe0, kwcount=2, kwstep=1, defs=0x7fcbf6d68658, defcount=<optimized out>, kwdefs=0x0, 
    closure=0x0, name=0x7fcbf6d568f0, qualname=0x7fcbf6d568f0)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4329
#36 0x00005602e485b559 in _PyFunction_Vectorcall (func=<optimized out>, stack=<optimized out>, 
    nargsf=<optimized out>, kwnames=<optimized out>) at /usr/local/src/conda/python-3.9.19/Objects/call.c:396
#37 0x00005602e484c162 in _PyObject_VectorcallTstate (kwnames=0x7fcbf6d6edc0, nargsf=<optimized out>, 
    args=<optimized out>, callable=0x7fcbc5e7e820, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Include/cpython/abstract.h:118
#38 PyObject_Vectorcall (kwnames=0x7fcbf6d6edc0, nargsf=<optimized out>, args=<optimized out>, 
    callable=0x7fcbc5e7e820) at /usr/local/src/conda/python-3.9.19/Include/cpython/abstract.h:127
#39 call_function (kwnames=0x7fcbf6d6edc0, oparg=<optimized out>, pp_stack=<synthetic pointer>, 
    tstate=<optimized out>) at /usr/local/src/conda/python-3.9.19/Python/ceval.c:5077
#40 _PyEval_EvalFrameDefault (tstate=<optimized out>, f=0x5602e4b2ea50, throwflag=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:3537
#41 0x00005602e484a184 in _PyEval_EvalFrame (throwflag=0, f=0x5602e4b2ea50, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Include/internal/pycore_ceval.h:40
#42 _PyEval_EvalCode (tstate=0x5602e4acc8b0, _co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kwnames=0x0, kwargs=0x0, kwcount=0, 
    kwstep=2, defs=0x0, defcount=<optimized out>, kwdefs=0x0, closure=0x0, name=0x0, qualname=0x0)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4329
#43 0x00005602e4849e58 in _PyEval_EvalCodeWithName (_co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kwnames=<optimized out>, kwargs=0x0, 
    kwcount=0, kwstep=2, defs=0x0, defcount=0, kwdefs=0x0, closure=0x0, name=0x0, qualname=0x0)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4361
#41 0x00005602e484a184 in _PyEval_EvalFrame (throwflag=0, f=0x5602e4b2ea50, tstate=0x5602e4acc8b0)
    at /usr/local/src/conda/python-3.9.19/Include/internal/pycore_ceval.h:40
#42 _PyEval_EvalCode (tstate=0x5602e4acc8b0, _co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kwnames=0x0, kwargs=0x0, kwcount=0, 
    kwstep=2, defs=0x0, defcount=<optimized out>, kwdefs=0x0, closure=0x0, name=0x0, qualname=0x0)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4329
#43 0x00005602e4849e58 in _PyEval_EvalCodeWithName (_co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kwnames=<optimized out>, kwargs=0x0, 
    kwcount=0, kwstep=2, defs=0x0, defcount=0, kwdefs=0x0, closure=0x0, name=0x0, qualname=0x0)
    at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4361
--Type <RET> for more, q to quit, c to continue without paging--
#44 0x00005602e4849e09 in PyEval_EvalCodeEx (_co=<optimized out>, globals=<optimized out>, 
    locals=<optimized out>, args=<optimized out>, argcount=<optimized out>, kws=<optimized out>, kwcount=0, 
    defs=0x0, defcount=0, kwdefs=0x0, closure=0x0) at /usr/local/src/conda/python-3.9.19/Python/ceval.c:4377
#45 0x00005602e48f74ab in PyEval_EvalCode (co=co@entry=0x7fcbf6d69710, globals=globals@entry=0x7fcbf70e3ac0, 
    locals=locals@entry=0x7fcbf70e3ac0) at /usr/local/src/conda/python-3.9.19/Python/ceval.c:828
#46 0x00005602e492487a in run_eval_code_obj (tstate=0x5602e4acc8b0, co=0x7fcbf6d69710, globals=0x7fcbf70e3ac0, 
    locals=0x7fcbf70e3ac0) at /usr/local/src/conda/python-3.9.19/Python/pythonrun.c:1221
#47 0x00005602e4920c03 in run_mod (mod=<optimized out>, filename=<optimized out>, globals=0x7fcbf70e3ac0, 
    locals=0x7fcbf70e3ac0, flags=<optimized out>, arena=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Python/pythonrun.c:1242
#48 0x00005602e47b4175 in pyrun_file (fp=0x5602e4b51b80, filename=0x7fcbf7026810, start=<optimized out>, 
    globals=0x7fcbf70e3ac0, locals=0x7fcbf70e3ac0, closeit=1, flags=0x7fffc6dbe7f8)
    at /usr/local/src/conda/python-3.9.19/Python/pythonrun.c:1140
#49 0x00005602e491a841 in pyrun_simple_file (flags=0x7fffc6dbe7f8, closeit=1, filename=0x7fcbf7026810, 
    fp=0x5602e4b51b80) at /usr/local/src/conda/python-3.9.19/Python/pythonrun.c:450
#50 PyRun_SimpleFileExFlags (fp=0x5602e4b51b80, filename=<optimized out>, closeit=1, flags=0x7fffc6dbe7f8)
    at /usr/local/src/conda/python-3.9.19/Python/pythonrun.c:483
#51 0x00005602e4917c6d in pymain_run_file (cf=0x7fffc6dbe7f8, config=0x5602e4acd190)
    at /usr/local/src/conda/python-3.9.19/Modules/main.c:377
#52 pymain_run_python (exitcode=0x7fffc6dbe7f0) at /usr/local/src/conda/python-3.9.19/Modules/main.c:602
#53 Py_RunMain () at /usr/local/src/conda/python-3.9.19/Modules/main.c:681
#54 0x00005602e48eb2e7 in Py_BytesMain (argc=<optimized out>, argv=<optimized out>)
    at /usr/local/src/conda/python-3.9.19/Modules/main.c:1101
#55 0x00007fcbf723f24d in __libc_start_main () from /lib64/libc.so.6
#56 0x00005602e48eb1e1 in _start ()

6 replies

sunggonkim Aug 5, 2024
Author

Output.txt

At this point, It seems like I cannot reproduce the error.
I believe this resolve is related to the recent perlmutter update but not share why.
When I execute the identical code, it runs well without an error (as depicted in the attached output file).

yangcal Aug 5, 2024
Maintainer

Interesting, so you can't reproduce the error now even without setting these environment variables? Did you know what update perlmutter did?

sunggonkim Aug 6, 2024
Author

This link has the lastest update.

In the log, they said that they removed "nvidia: removed 22.2", which may have impacted the code.
But I am really not sure the exact update they have done.

Here are the outputs for conda list and pip list, just for the reference.
condalist.txt
piplist.txt

yangcal Aug 6, 2024
Maintainer

I assume that nvidia 22.2 refers to the 22.2 SDK which contains the entire toolkit but only for CUDA 11. Perhaps that module is somehow interfering with the cuda12.5 that you got from conda installation of cuquantum-python. In any case, I'm glad that it's resolved.

Answer selected by sunggonkim

sunggonkim Aug 6, 2024
Author

Thanks for the help throughout this journey :)

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Floating point error with MPS Simulator. During contract_decompose function call. #147

sunggonkim Jul 27, 2024

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