numba: CudaSupportError: Error at driver init: [100] Call to cuInit results in CUDA_ERROR_NO_DEVICE:

Hi,

I’m getting this error when using numba. I have installed rapids.ai on WSL2 with ubuntu 20.04. Rapids GPU packages are working with the GPU. I can load a dataframe into the GPU with cuDF and perform basic calculations with no problem.

However, when I try to use something that requires numba I get this error:


from numba import cuda
print(cuda.gpus)

---------------------------------------------------------------------------
CudaAPIError                              Traceback (most recent call last)
~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/driver.py in initialize(self)
    236             _logger.info('init')
--> 237             self.cuInit(0)
    238         except CudaAPIError as e:

~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/driver.py in safe_cuda_api_call(*args)
    299             retcode = libfn(*args)
--> 300             self._check_error(fname, retcode)
    301         return safe_cuda_api_call

~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/driver.py in _check_error(self, fname, retcode)
    334                     raise CudaDriverError("CUDA initialized before forking")
--> 335             raise CudaAPIError(retcode, msg)
    336 

CudaAPIError: [100] Call to cuInit results in CUDA_ERROR_NO_DEVICE

During handling of the above exception, another exception occurred:

CudaSupportError                          Traceback (most recent call last)
<ipython-input-1-87434641e75b> in <module>
      1 from numba import cuda
----> 2 print(cuda.gpus)

~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/devices.py in __str__(self)
     41 
     42     def __str__(self):
---> 43         return ', '.join([str(d) for d in self.lst])
     44 
     45     def __iter__(self):

~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/devices.py in __getattr__(self, attr)
     24             # Device list is not initialized.
     25             # Query all CUDA devices.
---> 26             numdev = driver.get_device_count()
     27             gpus = [_DeviceContextManager(driver.get_device(devid))
     28                     for devid in range(numdev)]

~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/driver.py in get_device_count(self)
    344     def get_device_count(self):
    345         count = c_int()
--> 346         self.cuDeviceGetCount(byref(count))
    347         return count.value
    348 

~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/driver.py in __getattr__(self, fname)
    278         # Initialize driver
    279         if not self.is_initialized:
--> 280             self.initialize()
    281 
    282         if self.initialization_error is not None:

~/miniconda3/envs/rapids-0.18/lib/python3.8/site-packages/numba/cuda/cudadrv/driver.py in initialize(self)
    238         except CudaAPIError as e:
    239             self.initialization_error = e
--> 240             raise CudaSupportError("Error at driver init: \n%s:" % e)
    241         else:
    242             self.pid = _getpid()

CudaSupportError: Error at driver init: 
[100] Call to cuInit results in CUDA_ERROR_NO_DEVICE:

When calling %%env there is no ‘CUDA_DEVICE_ORDER’: , or ‘CUDA_VISIBLE_DEVICES’:

If I add these (the RTX 8000 is nr 0): `import os

os.environ[“CUDA_VISIBLE_DEVICES”]=“0”`

Still same Error.

I have tested this in numba 0.52.0 and the latest dev with the same issue (0.53.rc2)

About this issue

Original URL
State: closed
Created 3 years ago
Comments: 24 (10 by maintainers)

Most upvoted comments

Hi, I had the same issue with cuml, cudf etc. versions 23.02 on WSL2, Windows 11 fresh install. However rapids versions 22.08 in another anaconda environment worked just fine. @gmarkall hints in this forum and discussion https://github.com/numba/numba/issues/7104 saved my day. Summary: as there is some confusion with installation instructions, especially cuda libraries, review your .bashrc on wsl2. sudo nano .bashrc

add these lines at the end of your .bashrc:

export LD_LIBRARY_PATH=“/usr/lib/wsl/lib/” export NUMBA_CUDA_DRIVER=“/usr/lib/wsl/lib/libcuda.so.1”

BEFORE exports of LD_LIBRARY_PATH and NUMBA_CUDA_DRIVER, because most likely there already is something like this: export LD_LIBRARY_PATH=/usr/local/cuda-11.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

save your .bashrc (ctrl^O enter ctrl^X from nano) At the prompt: source .bashrc start your spyder or anaconda and then set the new environment console. From GUI you run: from numba import cuda cuda.detect() you should get info about your GPU. If you still get the error, continue looking for mistakes in cuda setup.

if this work around helped, after you type !numba -s you should look for CUDA Information CUDA Device Initialized : True CUDA Driver Version : your version here

Best regards!

viktorasb on Apr 3, 2023

I will do this as soon as a fix is released for the newest windows preview build affecting the GPU (https://answers.microsoft.com/en-us/insider/forum/all/version-21327-impacts-nvidia-on-wsl-2/413e96d1-0f62-41de-902e-500fab919427?page=2)

torstendahlen on Mar 10, 2021

`System info:

Time Stamp Report started (local time) : 2021-03-01 20:24:02.694366 UTC start time : 2021-03-01 19:24:02.694370 Running time (s) : 2.639743

Hardware Information Machine : x86_64 CPU Name : skylake-avx512 CPU Count : 24 Number of accessible CPUs : 24 List of accessible CPUs cores : 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 CFS Restrictions (CPUs worth of runtime) : None

CPU Features : 64bit adx aes avx avx2 avx512bw avx512cd avx512dq avx512f avx512vl bmi bmi2 clflushopt clwb cmov cx16 cx8 f16c fma fsgsbase fxsr invpcid lzcnt mmx movbe pclmul popcnt prfchw rdrnd rdseed rtm sahf sse sse2 sse3 sse4.1 sse4.2 ssse3 xsave xsavec xsaveopt xsaves

Memory Total (MB) : 128677 Memory Available (MB) : 127059

OS Information Platform Name : Linux-5.4.91-microsoft-standard-WSL2-x86_64-with-glibc2.10 Platform Release : 5.4.91-microsoft-standard-WSL2 OS Name : Linux OS Version : #1 SMP Mon Jan 25 18:39:31 UTC 2021 OS Specific Version : ? Libc Version : glibc 2.31

Python Information Python Compiler : GCC 9.3.0 Python Implementation : CPython Python Version : 3.8.8 Python Locale : en_US.UTF-8

LLVM Information LLVM Version : 10.0.1

CUDA Information CUDA Device Initialized : False CUDA Driver Version : ? CUDA Detect Output: None CUDA Librairies Test Output: None

ROC information ROC Available : False ROC Toolchains : None HSA Agents Count : 0 HSA Agents: None HSA Discrete GPUs Count : 0 HSA Discrete GPUs : None

SVML Information SVML State, config.USING_SVML : False SVML Library Loaded : False llvmlite Using SVML Patched LLVM : True SVML Operational : False

Threading Layer Information TBB Threading Layer Available : False ±-> Disabled due to Unknown import problem. OpenMP Threading Layer Available : True ±->Vendor: GNU Workqueue Threading Layer Available : True ±->Workqueue imported successfully.

Numba Environment Variable Information None found.

Conda Information Conda Build : not installed Conda Env : 4.9.2 Conda Platform : linux-64 Conda Python Version : 3.8.5.final.0 Conda Root Writable : True

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No errors reported.

Warning log Warning (cuda): CUDA device intialisation problem. Message:Error at driver init: [100] Call to cuInit results in CUDA_ERROR_NO_DEVICE: Exception class: <class ‘numba.cuda.cudadrv.error.CudaSupportError’> Warning (roc): Error initialising ROC: No ROC toolchains found. Warning (roc): No HSA Agents found, encountered exception when searching: Error at driver init: NUMBA_HSA_DRIVER /opt/rocm/lib/libhsa-runtime64.so is not a valid file path. Note it must be a filepath of the .so/.dll/.dylib or the driver: Warning (no file): /sys/fs/cgroup/cpuacct/cpu.cfs_quota_us Warning (no file): /sys/fs/cgroup/cpuacct/cpu.cfs_period_us

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torstendahlen on Mar 1, 2021