On Ubuntu-based NVIDIA docker image, container does NOT recognize GPU but Redhat-based container does. Why? I followed the official installation manual and used the official docker image. Should I ask about it to NVIDIA?
Environment
- Ubuntu Desktop 22.04 LTS
- Docker 20.10.21
- GPU RTX 2080
- Driver nvidia-driver-510
- No CUDA installed on host OS
Command
# Ubuntu cuda11.8
$ docker run --gpus all -it --rm nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04 /bin/bash
$ nvidia-smi
$ nvcc -V
bash: nvcc: command not found
$ apt-get update
$ apt-get install -y python3 python3-pip
$ pip3 install torch torchvision
$ python3
Python 3.10.6 (main, Aug 10 2022, 11:40:04) [GCC 11.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.cuda.is_available())
/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py:88: UserWarning: CUDA initialization: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 804: forward compatibility was attempted on non supported HW (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:109.)
return torch._C._cuda_getDeviceCount() > 0
False
# Ubuntu cuda11.6
$ docker run --gpus all -it --rm nvidia/cuda:11.6.1-cudnn8-runtime-ubuntu20.04 /bin/bash
$ nvidia-smi
$ nvcc -V
bash: nvcc: command not found
# Redhat cuda11.6
$ docker run --gpus all -it --rm nvidia/cuda:11.6.1-cudnn8-devel-ubi8 /bin/bash
$ nvidia-smi
$ nvcc -V
$ yum install python38
$ curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
$ python3 get-pip.py
$ pip install torch torchvision
$ python3
Python 3.8.12 (default, Sep 16 2021, 10:46:05)
[GCC 8.5.0 20210514 (Red Hat 8.5.0-3)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.cuda.is_available())
True
>>>
Ref
