Comments (4)
and ... as is typical, after I post on an issue I remember something ... I had channel_priority: strict
in my .condarc
. I recall seeing in the RAPIDS docs that you shouldn't do this, so I commented it out and re-ran the install of the nightly build ... voila, no error!
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Hooray! Thanks for the update @ktyle . Closing, and hoping others who are facing a similar challenge find this solution :)
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Thanks for the report. When I cloned this repo on SMSL and ran the same command just now things worked as expected.
Could you share the full output from your command, the contents of your environment file, the output of running nvidia-smi
at the terminal, and your version of mamba in the base/studiolab environment from which you're running the command?
from rapids-smsl.
Hah, @rsignell-usgs, we're (somewhat) in sync ...
Although not on SMSL, I notice a similar error when I attempt either the stable 22.06 or nightly 22.08. This is on a freshly-installed environment using Mambaforge 4.12.0.2 (Linux x86_64) on a Dell PowerEdge R940xa with two Tesla V100S GPUs.
Requested outputs below:
nvidia-smi
Mon Jul 18 19:07:15 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.129.06 Driver Version: 470.129.06 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla V100S-PCI... Off | 00000000:25:00.0 Off | 0 |
| N/A 40C P0 36W / 250W | 0MiB / 32510MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 Tesla V100S-PCI... Off | 00000000:C8:00.0 Off | 0 |
| N/A 40C P0 38W / 250W | 0MiB / 32510MiB | 2% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
mamba create -n rapids-22.06 -c rapidsai -c nvidia -c conda-forge rapids=22.06 python=3.9 cudatoolkit=11.4 jupyterlab dask-sql
Looking for: ['rapids=22.06', 'python=3.9', 'cudatoolkit=11.4', 'jupyterlab', 'dask-sql']
conda-forge/linux-64 Using cache
conda-forge/noarch Using cache
rapidsai/noarch No change
nvidia/linux-64 No change
rapidsai/linux-64 No change
nvidia/noarch No change
Encountered problems while solving:
- package rapids-22.06.00-cuda11_py38_ged167d1_108 requires cupy >=9.5.0,<11.0.0a0, but none of the providers can be installed
mamba list
# packages in environment at /free1/ktyle/mambaforge:
#
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
brotlipy 0.7.0 py39hb9d737c_1004 conda-forge
bzip2 1.0.8 h7f98852_4 conda-forge
c-ares 1.18.1 h7f98852_0 conda-forge
ca-certificates 2022.6.15 ha878542_0 conda-forge
certifi 2022.6.15 py39hf3d152e_0 conda-forge
cffi 1.15.1 py39he91dace_0 conda-forge
charset-normalizer 2.1.0 pyhd8ed1ab_0 conda-forge
colorama 0.4.5 pyhd8ed1ab_0 conda-forge
conda 4.13.0 py39hf3d152e_1 conda-forge
conda-package-handling 1.8.1 py39hb9d737c_1 conda-forge
cryptography 37.0.4 py39hd97740a_0 conda-forge
cudatoolkit 11.7.0 hd8887f6_10 conda-forge
cupy 10.6.0 py39hc3c280e_0 conda-forge
fastrlock 0.8 py39h5a03fae_2 conda-forge
icu 70.1 h27087fc_0 conda-forge
idna 3.3 pyhd8ed1ab_0 conda-forge
keyutils 1.6.1 h166bdaf_0 conda-forge
krb5 1.19.3 h3790be6_0 conda-forge
ld_impl_linux-64 2.36.1 hea4e1c9_2 conda-forge
libarchive 3.5.2 hb890918_3 conda-forge
libblas 3.9.0 15_linux64_openblas conda-forge
libcblas 3.9.0 15_linux64_openblas conda-forge
libcurl 7.83.1 h7bff187_0 conda-forge
libedit 3.1.20191231 he28a2e2_2 conda-forge
libev 4.33 h516909a_1 conda-forge
libffi 3.4.2 h7f98852_5 conda-forge
libgcc-ng 12.1.0 h8d9b700_16 conda-forge
libgfortran-ng 12.1.0 h69a702a_16 conda-forge
libgfortran5 12.1.0 hdcd56e2_16 conda-forge
libgomp 12.1.0 h8d9b700_16 conda-forge
libiconv 1.16 h516909a_0 conda-forge
liblapack 3.9.0 15_linux64_openblas conda-forge
libmamba 0.24.0 hd8a31e3_1 conda-forge
libmambapy 0.24.0 py39hd55135b_1 conda-forge
libnghttp2 1.47.0 h727a467_0 conda-forge
libnsl 2.0.0 h7f98852_0 conda-forge
libopenblas 0.3.20 pthreads_h78a6416_0 conda-forge
libsolv 0.7.22 h6239696_0 conda-forge
libssh2 1.10.0 ha56f1ee_2 conda-forge
libstdcxx-ng 12.1.0 ha89aaad_16 conda-forge
libuuid 2.32.1 h7f98852_1000 conda-forge
libxml2 2.9.14 h22db469_3 conda-forge
libzlib 1.2.12 h166bdaf_2 conda-forge
lz4-c 1.9.3 h9c3ff4c_1 conda-forge
lzo 2.10 h516909a_1000 conda-forge
mamba 0.24.0 py39hfa8f2c8_1 conda-forge
ncurses 6.3 h27087fc_1 conda-forge
numpy 1.23.1 py39hba7629e_0 conda-forge
openssl 1.1.1q h166bdaf_0 conda-forge
pip 22.1.2 pyhd8ed1ab_0 conda-forge
pybind11-abi 4 hd8ed1ab_3 conda-forge
pycosat 0.6.3 py39hb9d737c_1010 conda-forge
pycparser 2.21 pyhd8ed1ab_0 conda-forge
pyopenssl 22.0.0 pyhd8ed1ab_0 conda-forge
pysocks 1.7.1 py39hf3d152e_5 conda-forge
python 3.9.13 h9a8a25e_0_cpython conda-forge
python_abi 3.9 2_cp39 conda-forge
readline 8.1.2 h0f457ee_0 conda-forge
reproc 14.2.3 h7f98852_0 conda-forge
reproc-cpp 14.2.3 h9c3ff4c_0 conda-forge
requests 2.28.1 pyhd8ed1ab_0 conda-forge
ruamel_yaml 0.15.80 py39hb9d737c_1007 conda-forge
setuptools 63.2.0 py39hf3d152e_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
sqlite 3.39.1 h4ff8645_0 conda-forge
tk 8.6.12 h27826a3_0 conda-forge
tqdm 4.64.0 pyhd8ed1ab_0 conda-forge
tzdata 2022a h191b570_0 conda-forge
urllib3 1.26.10 pyhd8ed1ab_0 conda-forge
wheel 0.37.1 pyhd8ed1ab_0 conda-forge
xz 5.2.5 h516909a_1 conda-forge
yaml 0.2.5 h7f98852_2 conda-forge
yaml-cpp 0.7.0 h27087fc_1 conda-forge
zlib 1.2.12 h166bdaf_2 conda-forge
zstd 1.5.2 h8a70e8d_2 conda-forge
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