[BUG] Dense PCA fails with CUDA12 #5555
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Intron7
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@Intron7 thanks for raising this issue. Is there a stack trace that you could share? |
@dantegd I hope that enough. I can also appended a nsys-report for cuda12 and cuda118 runs. |
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It seems like the bug still persists in rapids-23.10 |
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Just to check up is there still work beeing done fixing this issue? As far as I can tell the bug still persists in 23.12 |
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Also wondering about this. It must be related to rapids because torch doesn't have an issue running the same calculation on one GPU. |
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This is still broken. Also in the development version for 24.04 |
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@dantegd So I did some more testing on this because this seems to mainly affect Ampere GPUs. Can this please be fixed. |
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@Intron7 no, this also affects H100's (Hopper). |
Open
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I submitted PR rapidsai/raft#2332 to fix this issue. It should be resolved by version 24.08 |
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@lowener Hi, I also had a similar problem in CUDA 12.1, I would like to ask if I need to choose 12.0? Traceback (most recent call last):
File "/app/r_sc_test.py", line 115, in <module>
rsc.tl.pca(adata, n_comps=100)
File "/usr/local/lib/python3.10/site-packages/rapids_singlecell/preprocessing/_pca.py", line 163, in pca
X_pca = pca_func.fit_transform(X)
File "/usr/local/lib/python3.10/site-packages/cuml/internals/api_decorators.py", line 188, in wrapper
ret = func(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/cuml/internals/api_decorators.py", line 393, in dispatch
return self.dispatch_func(func_name, gpu_func, *args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/cuml/internals/api_decorators.py", line 190, in wrapper
return func(*args, **kwargs)
File "base.pyx", line 687, in cuml.internals.base.UniversalBase.dispatch_func
File "pca.pyx", line 507, in cuml.decomposition.pca.PCA.fit_transform
File "/usr/local/lib/python3.10/site-packages/cuml/internals/api_decorators.py", line 188, in wrapper
ret = func(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/cuml/internals/api_decorators.py", line 393, in dispatch
return self.dispatch_func(func_name, gpu_func, *args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/cuml/internals/api_decorators.py", line 190, in wrapper
return func(*args, **kwargs)
File "base.pyx", line 687, in cuml.internals.base.UniversalBase.dispatch_func
File "pca.pyx", line 468, in cuml.decomposition.pca.PCA.fit
RuntimeError: cuSOLVER error encountered at: file=/__w/cuml/cuml/python/build/cp310-cp310-linux_x86_64/_deps/raft-src/cpp/include/raft/linalg/detail/eig.cuh line=121: call='cusolverDnxsyevd(cusolverH, dn_params, CUSOLVER_EIG_MODE_VECTOR, CUBLAS_FILL_MODE_UPPER, static_cast<int64_t>(n_rows), eig_vectors, static_cast<int64_t>(n_cols), eig_vals, d_work.data(), workspaceDevice, h_work.data(), workspaceHost, d_dev_info.data(), stream)', Reason=7:CUSOLVER_STATUS_INTERNAL_ERROR
Obtained 42 stack frames
#1 in /usr/local/lib/python3.10/site-packages/cuml/internals/../libcuml++.so: raft::cusolver_error::cusolver_error(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) +0xbd [0x7f301aaa289d]
#2 in /usr/local/lib/python3.10/site-packages/cuml/internals/../libcuml++.so: void raft::linalg::detail::eigDC<float>(raft::resources const&, float const*, unsigned long, unsigned long, float*, float*, CUstream_st*) +0xe6b [0x7f301b0468fb]
#3 in /usr/local/lib/python3.10/site-packages/cuml/internals/../libcuml++.so: void ML::truncCompExpVars<float, ML::solver>(raft::handle_t const&, float*, float*, float*, float*, ML::paramsTSVDTemplate<ML::solver> const&, CUstream_st*) +0x5de [0x7f301b5f579e]
#4 in /usr/local/lib/python3.10/site-packages/cuml/internals/../libcuml++.so(+0x2cb60c5) [0x7f301b5e90c5]
#5 in /usr/local/lib/python3.10/site-packages/cuml/decomposition/pca.cpython-310-x86_64-linux-gnu.so(+0x3fedb) [0x7f2fe3c8eedb]
#6 in /usr/local/lib/python3.10/site-packages/cuml/internals/base.cpython-310-x86_64-linux-gnu.so(+0x1006e) [0x7f2fe455006e]
#7 in /usr/local/lib/python3.10/site-packages/cuml/internals/base.cpython-310-x86_64-linux-gnu.so(+0x2e7a6) [0x7f2fe456e7a6]
#8 in python: PyVectorcall_Call +0x6c [0x55ee4702169c]
#9 in python: _PyEval_EvalFrameDefault +0x44c6 [0x55ee47008c06]
#10 in python(+0x131d08) [0x55ee470dad08]
#11 in python(+0x2248c1) [0x55ee471cd8c1]
#12 in python: PyVectorcall_Call +0x6c [0x55ee4702169c]
#13 in python: _PyEval_EvalFrameDefault +0x44c6 [0x55ee47008c06]
#14 in python(+0x131d08) [0x55ee470dad08]
#15 in python: PyVectorcall_Call +0x6c [0x55ee4702169c]
#16 in python: _PyEval_EvalFrameDefault +0x44c6 [0x55ee47008c06]
#17 in python(+0x131d08) [0x55ee470dad08]
#18 in /usr/local/lib/python3.10/site-packages/cuml/decomposition/pca.cpython-310-x86_64-linux-gnu.so(+0x305d5) [0x7f2fe3c7f5d5]
#19 in /usr/local/lib/python3.10/site-packages/cuml/internals/base.cpython-310-x86_64-linux-gnu.so(+0x1006e) [0x7f2fe455006e]
#20 in /usr/local/lib/python3.10/site-packages/cuml/internals/base.cpython-310-x86_64-linux-gnu.so(+0x2e7a6) [0x7f2fe456e7a6]
#21 in python: PyVectorcall_Call +0x6c [0x55ee4702169c]
#22 in python: _PyEval_EvalFrameDefault +0x44c6 [0x55ee47008c06]
|
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Describe the bug
Dense PCA fails for larger Datasets with the following error.
RuntimeError: cuSOLVER error encountered at: file=/home/sdicks/micromamba/envs/rapids-23.08_12/include/raft/linalg/detail/eig.cuh line=118:
With CUDA 11.8 and Rapids-23.08 it works.
Steps/Code to reproduce bug
Expected behavior
That it work like cuml 23.08 with cuda11-8
Environment details (please complete the following information):
List of packages in environment: "/home/sdicks/micromamba/envs/rapids-23.08_12"
Name Version Build Channel
───────────────────────────────────────────────────────────────────────────────────────────────
_libgcc_mutex 0.1 conda_forge conda-forge
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anyio 3.7.1 pyhd8ed1ab_0 conda-forge
aom 3.5.0 h27087fc_0 conda-forge
appdirs 1.4.4 pyh9f0ad1d_0 conda-forge
argon2-cffi 21.3.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py310h5764c6d_3 conda-forge
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aws-c-auth 0.7.0 hbbaa140_3 conda-forge
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cucim 23.08.00 cuda12_py310_230809_gf3a294b_0 rapidsai
cuda-cccl 12.2.128 0 nvidia
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cuda-python 12.2.0 py310h79c70a0_0 nvidia
cuda-version 12.0 hffde075_2 conda-forge
cudf 23.08.00 cuda12_py310_230809_g8150d38e08_0 rapidsai
cudf_kafka 23.08.00 cuda12_py310_230809_g8150d38e08_0 rapidsai
cudnn 8.8.0.121 h459966d_1 conda-forge
cugraph 23.08.00 cuda12_py310_230809_g3079227b_0 rapidsai
cuml 23.08.00 cuda12_py310_230809_gd7162cdea_0 rapidsai
cuproj 23.08.01 cuda12_py310_230810_g2660aba7_0 rapidsai
cupy 12.1.0 py310hfc31588_1 conda-forge
curl 8.2.1 hca28451_0 conda-forge
cusparselt 0.4.0.7 h3a97aeb_2 conda-forge
cuspatial 23.08.01 cuda12_py310_230810_g2660aba7_0 rapidsai
custreamz 23.08.00 cuda12_py310_230809_g8150d38e08_0 rapidsai
cutensor 1.7.0.1 0 nvidia
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libstdcxx-ng 13.1.0 hfd8a6a1_0 conda-forge
libthrift 0.18.1 h8fd135c_2 conda-forge
libtiff 4.5.1 h8b53f26_0 conda-forge
libutf8proc 2.8.0 h166bdaf_0 conda-forge
libuuid 2.38.1 h0b41bf4_0 conda-forge
libuv 1.44.2 hd590300_1 conda-forge
libwebp 1.3.1 hbf2b3c1_0 conda-forge
libwebp-base 1.3.1 hd590300_0 conda-forge
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libxgboost 1.7.4 rapidsai_hbb0ba15_6 rapidsai
libxml2 2.11.5 h0d562d8_0 conda-forge
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libzopfli 1.0.3 h9c3ff4c_0 conda-forge
linkify-it-py 2.0.0 pyhd8ed1ab_0 conda-forge
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locket 1.0.0 pyhd8ed1ab_0 conda-forge
louvain 0.8.1 py310hc6cd4ac_0 conda-forge
lz4 4.3.2 py310h0cfdcf0_0 conda-forge
lz4-c 1.9.4 hcb278e6_0 conda-forge
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mapclassify 2.5.0 pyhd8ed1ab_1 conda-forge
markdown 3.4.4 pyhd8ed1ab_0 conda-forge
markdown-it-py 3.0.0 pyhd8ed1ab_0 conda-forge
markupsafe 2.1.3 py310h2372a71_0 conda-forge
matplotlib-base 3.7.2 py310hf38f957_0 conda-forge
matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge
mdit-py-plugins 0.4.0 pyhd8ed1ab_0 conda-forge
mdurl 0.1.0 pyhd8ed1ab_0 conda-forge
metis 5.1.1 h59595ed_0 conda-forge
mistune 3.0.0 pyhd8ed1ab_0 conda-forge
mpfr 4.2.0 hb012696_0 conda-forge
msgpack-python 1.0.5 py310hdf3cbec_0 conda-forge
multidict 6.0.4 py310h1fa729e_0 conda-forge
multipledispatch 0.6.0 py_0 conda-forge
munch 4.0.0 pyhd8ed1ab_0 conda-forge
munkres 1.1.4 pyh9f0ad1d_0 conda-forge
nbclient 0.8.0 pyhd8ed1ab_0 conda-forge
nbconvert-core 7.7.3 pyhd8ed1ab_0 conda-forge
nbformat 5.9.2 pyhd8ed1ab_0 conda-forge
nccl 2.18.3.1 h3a97aeb_0 conda-forge
ncurses 6.4 hcb278e6_0 conda-forge
nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge
networkx 3.1 pyhd8ed1ab_0 conda-forge
nodejs 20.1.0 hf52ce11_0 conda-forge
notebook-shim 0.2.3 pyhd8ed1ab_0 conda-forge
nspr 4.35 h27087fc_0 conda-forge
nss 3.89 he45b914_0 conda-forge
numba 0.57.1 py310h0f6aa51_0 conda-forge
numpy 1.24.4 py310ha4c1d20_0 conda-forge
nvcomp 2.6.1 h3a97aeb_2 conda-forge
nvtx 0.2.5 py310h1fa729e_0 conda-forge
openjpeg 2.5.0 hfec8fc6_2 conda-forge
openslide 3.4.1 ha896ae7_9 conda-forge
openssl 3.1.2 hd590300_0 conda-forge
orc 1.9.0 h385abfd_1 conda-forge
overrides 7.4.0 pyhd8ed1ab_0 conda-forge
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pandas 1.5.3 py310h9b08913_1 conda-forge
pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge
panel 1.2.1 pyhd8ed1ab_0 conda-forge
param 1.13.0 pyh1a96a4e_0 conda-forge
parso 0.8.3 pyhd8ed1ab_0 conda-forge
partd 1.4.0 pyhd8ed1ab_0 conda-forge
pcre2 10.40 hc3806b6_0 conda-forge
pexpect 4.8.0 pyh1a96a4e_2 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pillow 10.0.0 py310h582fbeb_0 conda-forge
pip 23.2.1 pyhd8ed1ab_0 conda-forge
pixman 0.40.0 h36c2ea0_0 conda-forge
pkgutil-resolve-name 1.3.10 pyhd8ed1ab_0 conda-forge
platformdirs 3.10.0 pyhd8ed1ab_0 conda-forge
pooch 1.7.0 pyha770c72_3 conda-forge
poppler 23.05.0 hd18248d_1 conda-forge
poppler-data 0.4.12 hd8ed1ab_0 conda-forge
postgresql 15.4 h8972f4a_0 conda-forge
proj 9.2.1 ha643af7_0 conda-forge
prometheus_client 0.17.1 pyhd8ed1ab_0 conda-forge
prompt-toolkit 3.0.39 pyha770c72_0 conda-forge
prompt_toolkit 3.0.39 hd8ed1ab_0 conda-forge
protobuf 4.23.3 py310hb875b13_0 conda-forge
psutil 5.9.5 py310h1fa729e_0 conda-forge
pthread-stubs 0.4 h36c2ea0_1001 conda-forge
ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
py-xgboost 1.7.4 rapidsai_py310h1395376_6 rapidsai
pyarrow 11.0.0 py310he6bfd7f_33_cpu conda-forge
pycparser 2.21 pyhd8ed1ab_0 conda-forge
pyct 0.4.6 py_0 conda-forge
pyct-core 0.4.6 py_0 conda-forge
pyee 8.1.0 pyhd8ed1ab_0 conda-forge
pygments 2.16.1 pyhd8ed1ab_0 conda-forge
pylibcugraph 23.08.00 cuda12_py310_230809_g3079227b_0 rapidsai
pylibraft 23.08.00 cuda12_py310_230809_ge588d7b5_0 rapidsai
pynvml 11.4.1 pyhd8ed1ab_0 conda-forge
pyopenssl 23.2.0 pyhd8ed1ab_1 conda-forge
pyparsing 3.0.9 pyhd8ed1ab_0 conda-forge
pyppeteer 1.0.2 pyhd8ed1ab_0 conda-forge
pyproj 3.6.0 py310h24ef57a_1 conda-forge
pysocks 1.7.1 pyha2e5f31_6 conda-forge
python 3.10.12 hd12c33a_0_cpython conda-forge
python-confluent-kafka 1.9.2 py310h5764c6d_2 conda-forge
python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
python-fastjsonschema 2.18.0 pyhd8ed1ab_0 conda-forge
python-igraph 0.10.6 py310h33b8572_0 conda-forge
python-json-logger 2.0.7 pyhd8ed1ab_0 conda-forge
python_abi 3.10 3_cp310 conda-forge
pytz 2023.3 pyhd8ed1ab_0 conda-forge
pyviz_comms 2.3.2 pyhd8ed1ab_0 conda-forge
pywavelets 1.4.1 py310h0a54255_0 conda-forge
pyyaml 6.0 py310h5764c6d_5 conda-forge
pyzmq 25.1.1 py310h5bbb5d0_0 conda-forge
raft-dask 23.08.00 cuda12_py310_230809_ge588d7b5_0 rapidsai
rapids 23.08.00 cuda12_py310_230809_g2a5b6f0_0 rapidsai
rapids-xgboost 23.08.00 cuda12_py310_230809_g2a5b6f0_0 rapidsai
rdma-core 28.9 h59595ed_1 conda-forge
re2 2023.03.02 h8c504da_0 conda-forge
readline 8.2 h8228510_1 conda-forge
referencing 0.30.2 pyhd8ed1ab_0 conda-forge
requests 2.31.0 pyhd8ed1ab_0 conda-forge
rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge
rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge
rmm 23.08.00 cuda12_py310_230809_gf3af0e8d_0 rapidsai
rocm-smi 5.6.0 h59595ed_1 conda-forge
rpds-py 0.9.2 py310hcb5633a_0 conda-forge
rtree 1.0.1 py310hbdcdc62_2 conda-forge
s2n 1.3.46 h06160fa_0 conda-forge
scikit-image 0.21.0 py310hc6cd4ac_0 conda-forge
scikit-learn 1.3.0 py310hf7d194e_0 conda-forge
scipy 1.11.1 py310ha4c1d20_0 conda-forge
send2trash 1.8.2 pyh41d4057_0 conda-forge
setuptools 68.0.0 pyhd8ed1ab_0 conda-forge
shapely 2.0.1 py310h056c13c_1 conda-forge
simpervisor 1.0.0 pyhd8ed1ab_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
snappy 1.1.10 h9fff704_0 conda-forge
sniffio 1.3.0 pyhd8ed1ab_0 conda-forge
sortedcontainers 2.4.0 pyhd8ed1ab_0 conda-forge
soupsieve 2.3.2.post1 pyhd8ed1ab_0 conda-forge
spdlog 1.11.0 h9b3ece8_1 conda-forge
sqlite 3.42.0 h2c6b66d_0 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
streamz 0.6.4 pyh6c4a22f_0 conda-forge
suitesparse 5.10.1 h9e50725_1 conda-forge
tbb 2021.10.0 h00ab1b0_0 conda-forge
tblib 1.7.0 pyhd8ed1ab_0 conda-forge
terminado 0.17.1 pyh41d4057_0 conda-forge
texttable 1.6.7 pyhd8ed1ab_0 conda-forge
threadpoolctl 3.2.0 pyha21a80b_0 conda-forge
tifffile 2023.7.18 pyhd8ed1ab_0 conda-forge
tiledb 2.13.2 hd532e3d_0 conda-forge
tinycss2 1.2.1 pyhd8ed1ab_0 conda-forge
tk 8.6.12 h27826a3_0 conda-forge
tomli 2.0.1 pyhd8ed1ab_0 conda-forge
toolz 0.12.0 pyhd8ed1ab_0 conda-forge
tornado 6.3.2 py310h2372a71_0 conda-forge
tqdm 4.66.1 pyhd8ed1ab_0 conda-forge
traitlets 5.9.0 pyhd8ed1ab_0 conda-forge
treelite 3.2.0 py310h1be96d9_0 conda-forge
typing-extensions 4.7.1 hd8ed1ab_0 conda-forge
typing_extensions 4.7.1 pyha770c72_0 conda-forge
typing_utils 0.1.0 pyhd8ed1ab_0 conda-forge
tzcode 2023c h0b41bf4_0 conda-forge
tzdata 2023c h71feb2d_0 conda-forge
uc-micro-py 1.0.1 pyhd8ed1ab_0 conda-forge
ucx 1.14.1 h195a15c_3 conda-forge
ucx-proc 1.0.0 gpu rapidsai
ucx-py 0.33.00 py310_230809_gea1eb8f_0 rapidsai
unicodedata2 15.0.0 py310h5764c6d_0 conda-forge
uri-template 1.3.0 pyhd8ed1ab_0 conda-forge
urllib3 1.26.15 pyhd8ed1ab_0 conda-forge
wcwidth 0.2.6 pyhd8ed1ab_0 conda-forge
webcolors 1.13 pyhd8ed1ab_0 conda-forge
webencodings 0.5.1 py_1 conda-forge
websocket-client 1.6.1 pyhd8ed1ab_0 conda-forge
websockets 10.4 py310h5764c6d_1 conda-forge
wheel 0.41.1 pyhd8ed1ab_0 conda-forge
xarray 2023.7.0 pyhd8ed1ab_0 conda-forge
xerces-c 3.2.4 h8d71039_2 conda-forge
xgboost 1.7.4 rapidsai_py310h1395376_6 rapidsai
xorg-kbproto 1.0.7 h7f98852_1002 conda-forge
xorg-libice 1.1.1 hd590300_0 conda-forge
xorg-libsm 1.2.4 h7391055_0 conda-forge
xorg-libx11 1.8.6 h8ee46fc_0 conda-forge
xorg-libxau 1.0.11 hd590300_0 conda-forge
xorg-libxdmcp 1.1.3 h7f98852_0 conda-forge
xorg-libxext 1.3.4 h0b41bf4_2 conda-forge
xorg-libxrender 0.9.11 hd590300_0 conda-forge
xorg-renderproto 0.11.1 h7f98852_1002 conda-forge
xorg-xextproto 7.3.0 h0b41bf4_1003 conda-forge
xorg-xproto 7.0.31 h7f98852_1007 conda-forge
xyzservices 2023.7.0 pyhd8ed1ab_0 conda-forge
xz 5.2.6 h166bdaf_0 conda-forge
yaml 0.2.5 h7f98852_2 conda-forge
yarl 1.9.2 py310h2372a71_0 conda-forge
zeromq 4.3.4 h9c3ff4c_1 conda-forge
zfp 1.0.0 h27087fc_3 conda-forge
zict 3.0.0 pyhd8ed1ab_0 conda-forge
zipp 3.16.2 pyhd8ed1ab_0 conda-forge
zlib 1.2.13 hd590300_5 conda-forge
zlib-ng 2.0.7 h0b41bf4_0 conda-forge
zstd 1.5.2 hfc55251_7 conda-forge
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