Zenn
Open7

Windows11 + WSL2 + Docker Desktop環境を作る

flowermenflowermen

とりあえず管理者権限のコマンドプロンプトでWSLをインストール

wsl --install

加えてWindowsの機能の有効化または無効化から、Linux用Windowsサブシステムを有効化して再起動

flowermenflowermen

古いGPGキー(GNU Privacy Guard: インストールしようとしているソフトウェアが本物か検証するためのキー)を削除する

sudo apt-key del 7fa2af80

Linux x86 CUDA toolkitのインストール

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda-repo-ubuntu2004-11-7-local_11.7.0-515.43.04-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2004-11-7-local_11.7.0-515.43.04-1_amd64.deb
wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt-get update
sudo apt-get -y install cuda-toolkit-11-7

dpkg: .debのファイルをインストールする

sudo dpkg -i cuda-keyring_1.0-1_all.debでブルスク落ちした

再起動後dpkg -lでcuda-keyringが入っていることを確認したので続行

インストールできてるか確認

/usr/local/cuda/bin/nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Tue_May__3_18:49:52_PDT_2022
Cuda compilation tools, release 11.7, V11.7.64
Build cuda_11.7.r11.7/compiler.31294372_0
flowermenflowermen

動作確認

docker pull tensorflow/tensorflow:latest-gpu
docker run --gpus all -it -p 8888:8888 tensorflow/tensorflow:latest-gpu
nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.73.08    Driver Version: 512.96       CUDA Version: 11.6     |
|-------------------------------+----------------------+----------------------+
| 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 ...  On   | 00000000:09:00.0  On |                  N/A |
| 41%   39C    P8    12W / 125W |    683MiB /  6144MiB |      4%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+


root@4a32b0ad9879:/# python3
Python 3.8.10 (default, Mar 15 2022, 12:22:08)
[GCC 9.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
>>> tensorflow.version
<module 'tensorflow._api.v2.version' from '/usr/local/lib/python3.8/dist-packages/tensorflow/_api/v2/version/__init__.py'>
>>> from tensorflow.python.client import device_lib
>>> device_lib.list_local_devices()
2022-06-09 10:30:16.773862: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-06-09 10:30:16.939314: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:961] could not open file to read NUMA node: /sys/bus/pci/devices/0000:09:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-06-09 10:30:16.949436: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:961] could not open file to read NUMA node: /sys/bus/pci/devices/0000:09:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-06-09 10:30:16.949754: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:961] could not open file to read NUMA node: /sys/bus/pci/devices/0000:09:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-06-09 10:30:17.632875: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:961] could not open file to read NUMA node: /sys/bus/pci/devices/0000:09:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-06-09 10:30:17.633230: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:961] could not open file to read NUMA node: /sys/bus/pci/devices/0000:09:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-06-09 10:30:17.633289: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Could not identify NUMA node of platform GPU id 0, defaulting to 0.  Your kernel may not have been built with NUMA support.
2022-06-09 10:30:17.633641: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:961] could not open file to read NUMA node: /sys/bus/pci/devices/0000:09:00.0/numa_node
Your kernel may have been built without NUMA support.
2022-06-09 10:30:17.633723: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /device:GPU:0 with 3954 MB memory:  -> device: 0, name: NVIDIA GeForce GTX 1660 SUPER, pci bus id: 0000:09:00.0, compute capability: 7.5
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 3105584825495753608
xla_global_id: -1
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 4146659328
locality {
  bus_id: 1
  links {
  }
}
incarnation: 2705822217186746394
physical_device_desc: "device: 0, name: NVIDIA GeForce GTX 1660 SUPER, pci bus id: 0000:09:00.0, compute capability: 7.5"
xla_global_id: 416903419
]