WSL2 + Docker Desktop で GPU を使用したい
WSL2 + Docker Desktop で GPU を使用したい
WSL、Docker 初心者です。
物体検出のため Docker 上で GPU を使いたいのですが、コンテナ起動時に The NVIDIA Driver was not detected. と出力されてしまいます。
Use 'nvidia-docker run' to start this container; と続くのですが、調べたところ Nvidia Docker ではなく後継の NVIDIA Container Toolkit を使う方法が多く、導入を済ませたのですが出力が変わりません。
初心者故に何から調べれば良いか分からず八方塞がりの状態です、どうかご教授お願いします。
出力
$ docker run -it --rm --gpus all --name="20.07-py3" nvcr.io/nvidia/pytorch:20.07-py3 nvidia-smi
=============
== PyTorch ==
=============
NVIDIA Release 20.07 (build 14714849.1)
PyTorch Version 1.6.0a0+9907a3e
Container image Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
Copyright (c) 2014-2020 Facebook Inc.
Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert)
Copyright (c) 2012-2014 Deepmind Technologies (Koray Kavukcuoglu)
Copyright (c) 2011-2012 NEC Laboratories America (Koray Kavukcuoglu)
Copyright (c) 2011-2013 NYU (Clement Farabet)
Copyright (c) 2006-2010 NEC Laboratories America (Ronan Collobert, Leon Bottou, Iain Melvin, Jason Weston)
Copyright (c) 2006 Idiap Research Institute (Samy Bengio)
Copyright (c) 2001-2004 Idiap Research Institute (Ronan Collobert, Samy Bengio, Johnny Mariethoz)
Copyright (c) 2015 Google Inc.
Copyright (c) 2015 Yangqing Jia
Copyright (c) 2013-2016 The Caffe contributors
All rights reserved.
Various files include modifications (c) NVIDIA CORPORATION. All rights reserved.
NVIDIA modifications are covered by the license terms that apply to the underlying project or file.
WARNING: The NVIDIA Driver was not detected. GPU functionality will not be available.
Use 'nvidia-docker run' to start this container; see
https://github.com/NVIDIA/nvidia-docker/wiki/nvidia-docker .
NOTE: MOFED driver for multi-node communication was not detected.
Multi-node communication performance may be reduced.
NOTE: The SHMEM allocation limit is set to the default of 64MB. This may be
insufficient for PyTorch. NVIDIA recommends the use of the following flags:
nvidia-docker run --ipc=host ...
Tue Jan 30 13:49:04 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 545.36 Driver Version: 546.33 CUDA Version: 12.3 |
|-----------------------------------------+----------------------+----------------------+
| 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 NVIDIA GeForce RTX 3060 Ti On | 00000000:01:00.0 On | N/A |
| 30% 31C P8 21W / 200W | 766MiB / 8192MiB | 22% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
| 0 N/A N/A 33 G /Xwayland N/A |
| 0 N/A N/A 36 G /Xwayland N/A |
| 0 N/A N/A 37 G /Xwayland N/A |
+---------------------------------------------------------------------------------------+
0 likes