GPU服务器安装显卡驱动、CUDA和cuDNN
GPU服务器安装cuda和cudnn
- 1. 服务器驱动安装
- 2. cuda安装
- 3. cudNN安装
- 4. 安装docker环境
- 5. 安装nvidia-docker2
- 5.1 ubuntu系统安装
- 5.2 centos系统安装
- 6. 测试docker容调用GPU服务
1. 服务器驱动安装
- 显卡驱动下载地址
- https://www.nvidia.cn/Download/index.aspx?lang=cn
- 显卡驱动安装完成后可以通过命令：nvidia-smi 查看驱动信息
- 显卡型号查看命令：lspci |grep -i vga
root@hk-MZ32-AR0-00:~# nvidia-smi
Fri Feb 10 17:27:58 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.106.00 Driver Version: 460.106.00 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| 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 T4 Off | 00000000:04:00.0 Off | 0 |
| N/A 46C P0 27W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 Tesla T4 Off | 00000000:06:00.0 Off | 0 |
| N/A 43C P0 28W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 Tesla T4 Off | 00000000:0D:00.0 Off | 0 |
| N/A 48C P0 28W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 Tesla T4 Off | 00000000:0F:00.0 Off | 0 |
| N/A 45C P0 26W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 4 Tesla T4 Off | 00000000:17:00.0 Off | 0 |
| N/A 48C P0 27W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 5 Tesla T4 Off | 00000000:19:00.0 Off | 0 |
| N/A 48C P0 28W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 6 Tesla T4 Off | 00000000:21:00.0 Off | 0 |
| N/A 45C P0 26W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 7 Tesla T4 Off | 00000000:23:00.0 Off | 0 |
| N/A 45C P0 27W / 70W | 0MiB / 15109MiB | 4% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------++-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
2. cuda安装
- CUDA安装的时候需要注意显卡的驱动版本
- 参考文档 ：接入附上一份
- 此次实验机的驱动版本是 460.106.00，我选用的版本是CUDA 11.0
- 下载地址：https://developer.nvidia.com/cuda-toolkit-archive
root@hk-MZ32-AR0-00:~# wget http://developer.download.nvidia.com/compute/cuda/11.0.2/local_installers/cuda_11.0.2_450.51.05_linux.run
--2023-01-29 19:55:42-- http://developer.download.nvidia.com/compute/cuda/11.0.2/local_installers/cuda_11.0.2_450.51.05_linux.run
Resolving developer.download.nvidia.com (developer.download.nvidia.com)... 152.199.39.144
Connecting to developer.download.nvidia.com (developer.download.nvidia.com)|152.199.39.144|:80... connected.
HTTP request sent, awaiting response... 301 Moved Permanently
Location: https://developer.download.nvidia.com/compute/cuda/11.0.2/local_installers/cuda_11.0.2_450.51.05_linux.run [following]
--2023-01-29 19:55:43-- https://developer.download.nvidia.com/compute/cuda/11.0.2/local_installers/cuda_11.0.2_450.51.05_linux.run
Connecting to developer.download.nvidia.com (developer.download.nvidia.com)|152.199.39.144|:443... connected.
HTTP request sent, awaiting response... 301 Moved Permanently
Location: https://developer.download.nvidia.cn/compute/cuda/11.0.2/local_installers/cuda_11.0.2_450.51.05_linux.run [following]
--2023-01-29 19:55:44-- https://developer.download.nvidia.cn/compute/cuda/11.0.2/local_installers/cuda_11.0.2_450.51.05_linux.run
Resolving developer.download.nvidia.cn (developer.download.nvidia.cn)... 125.64.2.195, 125.64.2.196, 150.138.231.66, ...
Connecting to developer.download.nvidia.cn (developer.download.nvidia.cn)|125.64.2.195|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 3066694836 (2.9G) [application/octet-stream]
Saving to: ‘cuda_11.0.2_450.51.05_linux.run’100%[=====================================================================================================================================>] 3,066,694,836 11.3MB/s in 4m 25s 2023-01-29 20:00:15 (11.0 MB/s) - ‘cuda_11.0.2_450.51.05_linux.run’ saved [3066694836/3066694836]3. cudNN安装
- 下载链接：https://developer.nvidia.com/rdp/cudnn-archive
- cudNN下载的时候也需要注意CUDA的版本，如下图红色框标注的版本
root@hk-MZ32-AR0-00:~# rzZMODEM Session started e50
------------------------ Sent cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz
root@hk-MZ32-AR0-00:~# tar -xvf cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_infer_static.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_infer_static_v8.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_train_static.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_train_static_v8.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_infer_static.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_infer_static_v8.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_train_static.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_train_static_v8.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_infer_static.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_infer_static_v8.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_train_static.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_train_static_v8.a
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn.so.8
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn.so
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn.so.8.7.0
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_infer.so.8
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_infer.so
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_infer.so.8.7.0
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_train.so.8
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_train.so
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_adv_train.so.8.7.0
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_infer.so
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_infer.so.8
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_infer.so.8.7.0
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_train.so
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_train.so.8.7.0
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_cnn_train.so.8
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_infer.so.8.7.0
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_infer.so
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_infer.so.8
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_train.so.8.7.0
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_train.so
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/libcudnn_ops_train.so.8
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_adv_infer_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_adv_train_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_backend_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_cnn_infer_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_cnn_train_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_ops_infer_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_ops_train_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_version_v8.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_adv_infer.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_adv_train.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_backend.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_cnn_infer.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_cnn_train.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_ops_infer.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_ops_train.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/cudnn_version.h
cudnn-linux-x86_64-8.7.0.84_cuda11-archive/LICENSE
root@hk-MZ32-AR0-00:~# ll cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/
总用量 2520176
drwxr-xr-x 2 25503 2174 4096 11月 22 04:14 ./
drwxr-xr-x 4 25503 2174 4096 11月 22 04:14 ../
lrwxrwxrwx 1 25503 2174 23 11月 22 03:58 libcudnn_adv_infer.so -> libcudnn_adv_infer.so.8*
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_adv_infer.so.8 -> libcudnn_adv_infer.so.8.7.0*
-rwxr-xr-x 1 25503 2174 130381904 11月 22 03:58 libcudnn_adv_infer.so.8.7.0*
-rw-r--r-- 1 25503 2174 132979922 11月 22 03:58 libcudnn_adv_infer_static.a
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_adv_infer_static_v8.a -> libcudnn_adv_infer_static.a
lrwxrwxrwx 1 25503 2174 23 11月 22 03:58 libcudnn_adv_train.so -> libcudnn_adv_train.so.8*
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_adv_train.so.8 -> libcudnn_adv_train.so.8.7.0*
-rwxr-xr-x 1 25503 2174 121095120 11月 22 03:58 libcudnn_adv_train.so.8.7.0*
-rw-r--r-- 1 25503 2174 123566296 11月 22 03:58 libcudnn_adv_train_static.a
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_adv_train_static_v8.a -> libcudnn_adv_train_static.a
lrwxrwxrwx 1 25503 2174 23 11月 22 03:58 libcudnn_cnn_infer.so -> libcudnn_cnn_infer.so.8*
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_cnn_infer.so.8 -> libcudnn_cnn_infer.so.8.7.0*
-rwxr-xr-x 1 25503 2174 639185544 11月 22 03:58 libcudnn_cnn_infer.so.8.7.0*
-rw-r--r-- 1 25503 2174 829548950 11月 22 03:58 libcudnn_cnn_infer_static.a
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_cnn_infer_static_v8.a -> libcudnn_cnn_infer_static.a
lrwxrwxrwx 1 25503 2174 23 11月 22 03:58 libcudnn_cnn_train.so -> libcudnn_cnn_train.so.8*
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_cnn_train.so.8 -> libcudnn_cnn_train.so.8.7.0*
-rwxr-xr-x 1 25503 2174 102197000 11月 22 03:58 libcudnn_cnn_train.so.8.7.0*
-rw-r--r-- 1 25503 2174 153525776 11月 22 03:58 libcudnn_cnn_train_static.a
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_cnn_train_static_v8.a -> libcudnn_cnn_train_static.a
lrwxrwxrwx 1 25503 2174 23 11月 22 03:58 libcudnn_ops_infer.so -> libcudnn_ops_infer.so.8*
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_ops_infer.so.8 -> libcudnn_ops_infer.so.8.7.0*
-rwxr-xr-x 1 25503 2174 97489336 11月 22 03:58 libcudnn_ops_infer.so.8.7.0*
-rw-r--r-- 1 25503 2174 100636906 11月 22 03:58 libcudnn_ops_infer_static.a
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_ops_infer_static_v8.a -> libcudnn_ops_infer_static.a
lrwxrwxrwx 1 25503 2174 23 11月 22 03:58 libcudnn_ops_train.so -> libcudnn_ops_train.so.8*
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_ops_train.so.8 -> libcudnn_ops_train.so.8.7.0*
-rwxr-xr-x 1 25503 2174 74703096 11月 22 03:58 libcudnn_ops_train.so.8.7.0*
-rw-r--r-- 1 25503 2174 75156862 11月 22 03:58 libcudnn_ops_train_static.a
lrwxrwxrwx 1 25503 2174 27 11月 22 03:58 libcudnn_ops_train_static_v8.a -> libcudnn_ops_train_static.a
lrwxrwxrwx 1 25503 2174 13 11月 22 03:58 libcudnn.so -> libcudnn.so.8*
lrwxrwxrwx 1 25503 2174 17 11月 22 03:58 libcudnn.so.8 -> libcudnn.so.8.7.0*
-rwxr-xr-x 1 25503 2174 150200 11月 22 03:58 libcudnn.so.8.7.0*root@hk-MZ32-AR0-00:~# ll cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/
总用量 448
drwxr-xr-x 2 25503 2174 4096 11月 22 04:14 ./
drwxr-xr-x 4 25503 2174 4096 11月 22 04:14 ../
-rw-r--r-- 1 25503 2174 29025 11月 22 03:58 cudnn_adv_infer.h
-rw-r--r-- 1 25503 2174 29025 11月 22 03:58 cudnn_adv_infer_v8.h
-rw-r--r-- 1 25503 2174 27700 11月 22 03:58 cudnn_adv_train.h
-rw-r--r-- 1 25503 2174 27700 11月 22 03:58 cudnn_adv_train_v8.h
-rw-r--r-- 1 25503 2174 24727 11月 22 03:58 cudnn_backend.h
-rw-r--r-- 1 25503 2174 24727 11月 22 03:58 cudnn_backend_v8.h
-rw-r--r-- 1 25503 2174 29083 11月 22 03:58 cudnn_cnn_infer.h
-rw-r--r-- 1 25503 2174 29083 11月 22 03:58 cudnn_cnn_infer_v8.h
-rw-r--r-- 1 25503 2174 10217 11月 22 03:58 cudnn_cnn_train.h
-rw-r--r-- 1 25503 2174 10217 11月 22 03:58 cudnn_cnn_train_v8.h
-rw-r--r-- 1 25503 2174 2968 11月 22 03:58 cudnn.h
-rw-r--r-- 1 25503 2174 49631 11月 22 03:58 cudnn_ops_infer.h
-rw-r--r-- 1 25503 2174 49631 11月 22 03:58 cudnn_ops_infer_v8.h
-rw-r--r-- 1 25503 2174 25733 11月 22 03:58 cudnn_ops_train.h
-rw-r--r-- 1 25503 2174 25733 11月 22 03:58 cudnn_ops_train_v8.h
-rw-r--r-- 1 25503 2174 2968 11月 22 03:58 cudnn_v8.h
-rw-r--r-- 1 25503 2174 3113 11月 22 03:58 cudnn_version.h
-rw-r--r-- 1 25503 2174 3113 11月 22 03:58 cudnn_version_v8.h
root@hk-MZ32-AR0-00:~# cp -P cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/* /usr/local/cuda/lib64/root@hk-MZ32-AR0-00:~# cp -P cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/* /usr/local/cuda/include/
root@hk-MZ32-AR0-00:~# ll /usr/local/cuda/lib64/libcudnn*
lrwxrwxrwx 1 root root 23 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_infer.so -> libcudnn_adv_infer.so.8*
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_infer.so.8 -> libcudnn_adv_infer.so.8.7.0*
-rwxr-xr-x 1 root root 130381904 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_infer.so.8.7.0*
-rw-r--r-- 1 root root 132979922 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_infer_static.a
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_infer_static_v8.a -> libcudnn_adv_infer_static.a
lrwxrwxrwx 1 root root 23 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_train.so -> libcudnn_adv_train.so.8*
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_train.so.8 -> libcudnn_adv_train.so.8.7.0*
-rwxr-xr-x 1 root root 121095120 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_train.so.8.7.0*
-rw-r--r-- 1 root root 123566296 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_train_static.a
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_adv_train_static_v8.a -> libcudnn_adv_train_static.a
lrwxrwxrwx 1 root root 23 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_infer.so -> libcudnn_cnn_infer.so.8*
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_infer.so.8 -> libcudnn_cnn_infer.so.8.7.0*
-rwxr-xr-x 1 root root 639185544 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_infer.so.8.7.0*
-rw-r--r-- 1 root root 829548950 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_infer_static.a
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_infer_static_v8.a -> libcudnn_cnn_infer_static.a
lrwxrwxrwx 1 root root 23 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_train.so -> libcudnn_cnn_train.so.8*
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_train.so.8 -> libcudnn_cnn_train.so.8.7.0*
-rwxr-xr-x 1 root root 102197000 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_train.so.8.7.0*
-rw-r--r-- 1 root root 153525776 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_train_static.a
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_cnn_train_static_v8.a -> libcudnn_cnn_train_static.a
lrwxrwxrwx 1 root root 23 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_infer.so -> libcudnn_ops_infer.so.8*
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_infer.so.8 -> libcudnn_ops_infer.so.8.7.0*
-rwxr-xr-x 1 root root 97489336 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_infer.so.8.7.0*
-rw-r--r-- 1 root root 100636906 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_infer_static.a
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_infer_static_v8.a -> libcudnn_ops_infer_static.a
lrwxrwxrwx 1 root root 23 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_train.so -> libcudnn_ops_train.so.8*
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_train.so.8 -> libcudnn_ops_train.so.8.7.0*
-rwxr-xr-x 1 root root 74703096 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_train.so.8.7.0*
-rw-r--r-- 1 root root 75156862 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_train_static.a
lrwxrwxrwx 1 root root 27 2月 10 17:39 /usr/local/cuda/lib64/libcudnn_ops_train_static_v8.a -> libcudnn_ops_train_static.a
lrwxrwxrwx 1 root root 13 2月 10 17:39 /usr/local/cuda/lib64/libcudnn.so -> libcudnn.so.8*
lrwxrwxrwx 1 root root 17 2月 10 17:39 /usr/local/cuda/lib64/libcudnn.so.8 -> libcudnn.so.8.7.0*
-rwxr-xr-x 1 root root 150200 2月 10 17:39 /usr/local/cuda/lib64/libcudnn.so.8.7.0*
root@hk-MZ32-AR0-00:~# ll /usr/local/cuda/lib64/libcudnn* | wc -l
33
root@hk-MZ32-AR0-00:~# ll cudnn-linux-x86_64-8.7.0.84_cuda11-archive/
include/ lib/ LICENSE
root@hk-MZ32-AR0-00:~# ll cudnn-linux-x86_64-8.7.0.84_cuda11-archive/lib/* |wc -l
33root@hk-MZ32-AR0-00:~# ll /usr/local/cuda/include/cudn*
-rw-r--r-- 1 root root 29025 2月 10 17:39 /usr/local/cuda/include/cudnn_adv_infer.h
-rw-r--r-- 1 root root 29025 2月 10 17:39 /usr/local/cuda/include/cudnn_adv_infer_v8.h
-rw-r--r-- 1 root root 27700 2月 10 17:39 /usr/local/cuda/include/cudnn_adv_train.h
-rw-r--r-- 1 root root 27700 2月 10 17:39 /usr/local/cuda/include/cudnn_adv_train_v8.h
-rw-r--r-- 1 root root 24727 2月 10 17:39 /usr/local/cuda/include/cudnn_backend.h
-rw-r--r-- 1 root root 24727 2月 10 17:39 /usr/local/cuda/include/cudnn_backend_v8.h
-rw-r--r-- 1 root root 29083 2月 10 17:39 /usr/local/cuda/include/cudnn_cnn_infer.h
-rw-r--r-- 1 root root 29083 2月 10 17:39 /usr/local/cuda/include/cudnn_cnn_infer_v8.h
-rw-r--r-- 1 root root 10217 2月 10 17:39 /usr/local/cuda/include/cudnn_cnn_train.h
-rw-r--r-- 1 root root 10217 2月 10 17:39 /usr/local/cuda/include/cudnn_cnn_train_v8.h
-rw-r--r-- 1 root root 2968 2月 10 17:39 /usr/local/cuda/include/cudnn.h
-rw-r--r-- 1 root root 49631 2月 10 17:39 /usr/local/cuda/include/cudnn_ops_infer.h
-rw-r--r-- 1 root root 49631 2月 10 17:39 /usr/local/cuda/include/cudnn_ops_infer_v8.h
-rw-r--r-- 1 root root 25733 2月 10 17:39 /usr/local/cuda/include/cudnn_ops_train.h
-rw-r--r-- 1 root root 25733 2月 10 17:39 /usr/local/cuda/include/cudnn_ops_train_v8.h
-rw-r--r-- 1 root root 2968 2月 10 17:39 /usr/local/cuda/include/cudnn_v8.h
-rw-r--r-- 1 root root 3113 2月 10 17:39 /usr/local/cuda/include/cudnn_version.h
-rw-r--r-- 1 root root 3113 2月 10 17:39 /usr/local/cuda/include/cudnn_version_v8.h
root@hk-MZ32-AR0-00:~# ll /usr/local/cuda/include/cudn* |wc -l
18
root@hk-MZ32-AR0-00:~# ll cudnn-linux-x86_64-8.7.0.84_cuda11-archive/include/* | wc -l
18
4. 安装docker环境
root@hk-MZ32-AR0-00:~# curl -fsSL https://mirrors.aliyun.com/docker-ce/linux/ubuntu/gpg | sudo apt-key add -root@hk-MZ32-AR0-00:~# add-apt-repository "deb [arch=amd64] https://mirrors.aliyun.com/docker-ce/linux/ubuntu $(lsb_release -cs) stable"root@hk-MZ32-AR0-00:~# apt-get -y install docker-ce
5. 安装nvidia-docker2
5.1 ubuntu系统安装
root@hk-MZ32-AR0-00:~# curl -s -L https://nvidia.github.io/nvidia-docker/$(. /etc/os-release;echo $ID$VERSION_ID)/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
deb https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/$(ARCH) /
#deb https://nvidia.github.io/libnvidia-container/experimental/ubuntu18.04/$(ARCH) /
deb https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu18.04/$(ARCH) /
#deb https://nvidia.github.io/nvidia-container-runtime/experimental/ubuntu18.04/$(ARCH) /
deb https://nvidia.github.io/nvidia-docker/ubuntu18.04/$(ARCH) /root@hk-MZ32-AR0-00:~# apt-get update
命中:1 http://mirrors.aliyun.com/ubuntu bionic InRelease
命中:2 https://mirrors.aliyun.com/docker-ce/linux/ubuntu focal InRelease
获取:3 http://mirrors.aliyun.com/ubuntu bionic-security InRelease [88.7 kB]
命中:4 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic InRelease
获取:5 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-updates InRelease [88.7 kB]
获取:6 http://mirrors.aliyun.com/ubuntu bionic-updates InRelease [88.7 kB]
获取:7 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-backports InRelease [83.3 kB]
获取:8 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 InRelease [1,484 B]
命中:9 https://packages.microsoft.com/ubuntu/18.04/prod bionic InRelease
获取:10 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-security InRelease [88.7 kB]
获取:11 http://mirrors.aliyun.com/ubuntu bionic-proposed InRelease [242 kB]
获取:12 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-proposed InRelease [242 kB]
命中:13 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu focal InRelease
命中:14 https://linux.teamviewer.com/deb stable InRelease
获取:15 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-updates/main i386 Packages [1,604 kB]
获取:16 http://mirrors.aliyun.com/ubuntu bionic-backports InRelease [83.3 kB]
获取:17 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-updates/main amd64 Packages [2,909 kB]
获取:18 http://mirrors.aliyun.com/ubuntu bionic-security/main amd64 DEP-11 Metadata [76.8 kB]
获取:19 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-updates/main amd64 DEP-11 Metadata [297 kB]
获取:20 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-updates/universe amd64 DEP-11 Metadata [302 kB]
获取:21 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-updates/multiverse amd64 DEP-11 Metadata [2,468 B]
获取:22 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-backports/main amd64 DEP-11 Metadata [8,108 B]
获取:23 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-backports/universe amd64 DEP-11 Metadata [10.0 kB]
获取:24 https://nvidia.github.io/libnvidia-container/stable/ubuntu22.04/amd64 InRelease [1,484 B]
获取:25 http://mirrors.aliyun.com/ubuntu bionic-security/universe amd64 DEP-11 Metadata [61.0 kB]
获取:26 http://mirrors.aliyun.com/ubuntu bionic-security/multiverse amd64 DEP-11 Metadata [2,464 B]
获取:27 http://mirrors.aliyun.com/ubuntu bionic-updates/main amd64 Packages [2,909 kB]
获取:28 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-security/main amd64 DEP-11 Metadata [76.8 kB]
获取:29 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-security/universe amd64 DEP-11 Metadata [61.1 kB]
获取:30 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-security/multiverse amd64 DEP-11 Metadata [2,464 B]
获取:31 https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu22.04/amd64 InRelease [1,481 B]
获取:32 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-proposed/main Sources [81.3 kB]
获取:33 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-proposed/main Translation-en [38.8 kB]
获取:34 https://nvidia.github.io/nvidia-docker/ubuntu22.04/amd64 InRelease [1,474 B]
获取:35 https://mirrors.tuna.tsinghua.edu.cn/ubuntu bionic-proposed/main amd64 DEP-11 Metadata [6,552 B]
获取:36 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 Packages [22.3 kB]
获取:37 https://nvidia.github.io/libnvidia-container/stable/ubuntu22.04/amd64 Packages [22.3 kB]
获取:38 https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu22.04/amd64 Packages [7,416 B]
获取:39 https://nvidia.github.io/nvidia-docker/ubuntu22.04/amd64 Packages [4,488 B]
获取:40 http://mirrors.aliyun.com/ubuntu bionic-updates/main i386 Packages [1,604 kB]
获取:41 http://mirrors.aliyun.com/ubuntu bionic-updates/main amd64 DEP-11 Metadata [297 kB]
获取:42 http://mirrors.aliyun.com/ubuntu bionic-updates/universe amd64 DEP-11 Metadata [302 kB]
获取:43 http://mirrors.aliyun.com/ubuntu bionic-updates/multiverse amd64 DEP-11 Metadata [2,468 B]
获取:44 http://mirrors.aliyun.com/ubuntu bionic-proposed/main Sources [81.3 kB]
获取:45 http://mirrors.aliyun.com/ubuntu bionic-proposed/main Translation-en [38.8 kB]
获取:46 http://mirrors.aliyun.com/ubuntu bionic-proposed/main amd64 DEP-11 Metadata [6,516 B]
获取:47 http://mirrors.aliyun.com/ubuntu bionic-backports/main amd64 DEP-11 Metadata [8,092 B]
获取:48 http://mirrors.aliyun.com/ubuntu bionic-backports/universe amd64 DEP-11 Metadata [10.1 kB]
已下载 11.9 MB，耗时 11秒 (1,115 kB/s)
正在读取软件包列表... 2%
正在读取软件包列表... 完成
root@test:/etc/apt/sources.list.d#
root@test:/etc/apt/sources.list.d# apt-get install nvidia-docker2
正在读取软件包列表... 完成
正在分析软件包的依赖关系树
正在读取状态信息... 完成
下列软件包是自动安装的并且现在不需要了：libevent-2.1-7 libnatpmp1 libxvmc1 transmission-common
使用'apt autoremove'来卸载它(它们)。
将会同时安装下列软件：libnvidia-container-tools libnvidia-container1 nvidia-container-toolkit nvidia-container-toolkit-base
下列【新】软件包将被安装：libnvidia-container-tools libnvidia-container1 nvidia-container-toolkit nvidia-container-toolkit-base nvidia-docker2
升级了 0 个软件包，新安装了 5 个软件包，要卸载 0 个软件包，有 80 个软件包未被升级。
需要下载 3,773 kB 的归档。
解压缩后会消耗 14.6 MB 的额外空间。
您希望继续执行吗？ [Y/n] y
获取:1 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 libnvidia-container1 1.12.0-1 [927 kB]
获取:2 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 libnvidia-container-tools 1.12.0-1 [24.5 kB]
获取:3 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 nvidia-container-toolkit-base 1.12.0-1 [2,066 kB]
获取:4 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 nvidia-container-toolkit 1.12.0-1 [750 kB]
获取:5 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 nvidia-docker2 2.12.0-1 [5,544 B]
已下载 3,773 kB，耗时 2分 13秒 (28.3 kB/s)
正在选中未选择的软件包 libnvidia-container1:amd64。
(正在读取数据库 ... 系统当前共安装有 202374 个文件和目录。)
准备解压 .../libnvidia-container1_1.12.0-1_amd64.deb ...
正在解压 libnvidia-container1:amd64 (1.12.0-1) ...
正在选中未选择的软件包 libnvidia-container-tools。
准备解压 .../libnvidia-container-tools_1.12.0-1_amd64.deb ...
正在解压 libnvidia-container-tools (1.12.0-1) ...
正在选中未选择的软件包 nvidia-container-toolkit-base。
准备解压 .../nvidia-container-toolkit-base_1.12.0-1_amd64.deb ...
正在解压 nvidia-container-toolkit-base (1.12.0-1) ...
正在选中未选择的软件包 nvidia-container-toolkit。
准备解压 .../nvidia-container-toolkit_1.12.0-1_amd64.deb ...
正在解压 nvidia-container-toolkit (1.12.0-1) ...
正在选中未选择的软件包 nvidia-docker2。
准备解压 .../nvidia-docker2_2.12.0-1_all.deb ...
正在解压 nvidia-docker2 (2.12.0-1) ...
正在设置 nvidia-container-toolkit-base (1.12.0-1) ...
正在设置 libnvidia-container1:amd64 (1.12.0-1) ...
正在设置 libnvidia-container-tools (1.12.0-1) ...
正在设置 nvidia-container-toolkit (1.12.0-1) ...
正在设置 nvidia-docker2 (2.12.0-1) ...
正在处理用于 libc-bin (2.31-0ubuntu9.7) 的触发器 ...root@hk-MZ32-AR0-00:~# systemctl restart docker5.2 centos系统安装
[root@bj ~]# sudo yum install -y nvidia-docker2
Loaded plugins: fastestmirror, product-id, search-disabled-repos, subscription-managerThis system is not registered with an entitlement server. You can use subscription-manager to register.Loading mirror speeds from cached hostfile
epel/x86_64/metalink | 6.2 kB 00:00:00 * base: mirrors.163.com* epel: mirrors.bfsu.edu.cn* extras: mirrors.ustc.edu.cn* updates: mirrors.ustc.edu.cn
base | 3.6 kB 00:00:00
docker-ce-stable | 3.5 kB 00:00:00
extras | 2.9 kB 00:00:00
libnvidia-container/x86_64/signature | 833 B 00:00:00
Retrieving key from https://nvidia.github.io/libnvidia-container/gpgkey
Importing GPG key 0xF796ECB0:Userid : "NVIDIA CORPORATION (Open Source Projects) <cudatools@nvidia.com>"Fingerprint: c95b 321b 61e8 8c18 09c4 f759 ddca e044 f796 ecb0From : https://nvidia.github.io/libnvidia-container/gpgkey
libnvidia-container/x86_64/signature | 2.1 kB 00:00:00 !!!
nvidia-container-runtime/x86_64/signature | 833 B 00:00:00
Retrieving key from https://nvidia.github.io/nvidia-container-runtime/gpgkey
Importing GPG key 0xF796ECB0:Userid : "NVIDIA CORPORATION (Open Source Projects) <cudatools@nvidia.com>"Fingerprint: c95b 321b 61e8 8c18 09c4 f759 ddca e044 f796 ecb0From : https://nvidia.github.io/nvidia-container-runtime/gpgkey
nvidia-container-runtime/x86_64/signature | 2.1 kB 00:00:00 !!!
nvidia-docker/x86_64/signature | 833 B 00:00:00
Retrieving key from https://nvidia.github.io/nvidia-docker/gpgkey
Importing GPG key 0xF796ECB0:Userid : "NVIDIA CORPORATION (Open Source Projects) <cudatools@nvidia.com>"Fingerprint: c95b 321b 61e8 8c18 09c4 f759 ddca e044 f796 ecb0From : https://nvidia.github.io/nvidia-docker/gpgkey
nvidia-docker/x86_64/signature | 2.1 kB 00:00:00 !!!
teamviewer/x86_64/signature | 867 B 00:00:00
teamviewer/x86_64/signature | 2.5 kB 00:00:00 !!!
updates | 2.9 kB 00:00:00
(1/3): nvidia-container-runtime/x86_64/primary | 11 kB 00:00:01
(2/3): nvidia-docker/x86_64/primary | 8.0 kB 00:00:01
(3/3): libnvidia-container/x86_64/primary | 27 kB 00:00:03
libnvidia-container 171/171
nvidia-container-runtime 71/71
nvidia-docker 54/54
Resolving Dependencies
--> Running transaction check
---> Package nvidia-docker2.noarch 0:2.11.0-1 will be installed
--> Processing Dependency: nvidia-container-toolkit >= 1.10.0-1 for package: nvidia-docker2-2.11.0-1.noarch
--> Running transaction check
---> Package nvidia-container-toolkit.x86_64 0:1.11.0-1 will be installed
--> Processing Dependency: nvidia-container-toolkit-base = 1.11.0-1 for package: nvidia-container-toolkit-1.11.0-1.x86_64
--> Processing Dependency: libnvidia-container-tools < 2.0.0 for package: nvidia-container-toolkit-1.11.0-1.x86_64
--> Processing Dependency: libnvidia-container-tools >= 1.11.0-1 for package: nvidia-container-toolkit-1.11.0-1.x86_64
--> Running transaction check
---> Package libnvidia-container-tools.x86_64 0:1.11.0-1 will be installed
--> Processing Dependency: libnvidia-container1(x86-64) >= 1.11.0-1 for package: libnvidia-container-tools-1.11.0-1.x86_64
--> Processing Dependency: libnvidia-container.so.1(NVC_1.0)(64bit) for package: libnvidia-container-tools-1.11.0-1.x86_64
--> Processing Dependency: libnvidia-container.so.1()(64bit) for package: libnvidia-container-tools-1.11.0-1.x86_64
---> Package nvidia-container-toolkit-base.x86_64 0:1.11.0-1 will be installed
--> Running transaction check
---> Package libnvidia-container1.x86_64 0:1.11.0-1 will be installed
--> Finished Dependency ResolutionDependencies Resolved=================================================================================================================================================================================Package Arch Version Repository Size
=================================================================================================================================================================================
Installing:nvidia-docker2 noarch 2.11.0-1 libnvidia-container 8.7 k
Installing for dependencies:libnvidia-container-tools x86_64 1.11.0-1 libnvidia-container 50 klibnvidia-container1 x86_64 1.11.0-1 libnvidia-container 1.0 Mnvidia-container-toolkit x86_64 1.11.0-1 libnvidia-container 780 knvidia-container-toolkit-base x86_64 1.11.0-1 libnvidia-container 2.5 MTransaction Summary
=================================================================================================================================================================================
Install 1 Package (+4 Dependent packages)Total download size: 4.3 M
Installed size: 12 M
Downloading packages:
(1/5): libnvidia-container-tools-1.11.0-1.x86_64.rpm | 50 kB 00:00:01
(2/5): libnvidia-container1-1.11.0-1.x86_64.rpm | 1.0 MB 00:00:03
(3/5): nvidia-container-toolkit-1.11.0-1.x86_64.rpm | 780 kB 00:00:03
(4/5): nvidia-docker2-2.11.0-1.noarch.rpm | 8.7 kB 00:00:00
(5/5): nvidia-container-toolkit-base-1.11.0-1.x86_64.rpm | 2.5 MB 00:00:43
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Total 94 kB/s | 4.3 MB 00:00:46
Running transaction check
Running transaction test
Transaction test succeeded
Running transactionInstalling : nvidia-container-toolkit-base-1.11.0-1.x86_64 1/5 Installing : libnvidia-container1-1.11.0-1.x86_64 2/5 Installing : libnvidia-container-tools-1.11.0-1.x86_64 3/5 Installing : nvidia-container-toolkit-1.11.0-1.x86_64 4/5 Installing : nvidia-docker2-2.11.0-1.noarch 5/5 Verifying : libnvidia-container1-1.11.0-1.x86_64 1/5 Verifying : nvidia-container-toolkit-base-1.11.0-1.x86_64 2/5 Verifying : nvidia-container-toolkit-1.11.0-1.x86_64 3/5 Verifying : libnvidia-container-tools-1.11.0-1.x86_64 4/5 Verifying : nvidia-docker2-2.11.0-1.noarch 5/5 Installed:nvidia-docker2.noarch 0:2.11.0-1 Dependency Installed:libnvidia-container-tools.x86_64 0:1.11.0-1 libnvidia-container1.x86_64 0:1.11.0-1 nvidia-container-toolkit.x86_64 0:1.11.0-1 nvidia-container-toolkit-base.x86_64 0:1.11.0-1Complete!
- 若是centos系统，需要用yum安装过nvidia-docker2，虽然已经安装过nvidia-container-toolkit，但是在容器中使用gpu的时候报错，更新安装 nvidia-container-toolkit
# 设置yum源：nvidia-container-toolkit.repo[root@bj ~]# distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
> && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.repo | tee /etc/yum.repos.d/nvidia-container-toolkit.repo
[libnvidia-container]
name=libnvidia-container
baseurl=https://nvidia.github.io/libnvidia-container/stable/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=1
gpgkey=https://nvidia.github.io/libnvidia-container/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt[libnvidia-container-experimental]
name=libnvidia-container-experimental
baseurl=https://nvidia.github.io/libnvidia-container/experimental/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=0
gpgkey=https://nvidia.github.io/libnvidia-container/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt[root@bj ~]# yum install -y nvidia-container-toolkit
Loaded plugins: fastestmirror, product-id, search-disabled-repos, subscription-managerThis system is not registered with an entitlement server. You can use subscription-manager to register.Repository libnvidia-container is listed more than once in the configuration
Repository libnvidia-container-experimental is listed more than once in the configuration
Loading mirror speeds from cached hostfile* base: mirrors.ustc.edu.cn* epel: mirrors.ustc.edu.cn* extras: mirrors.ustc.edu.cn* updates: mirrors.ustc.edu.cn
Resolving Dependencies
--> Running transaction check
---> Package nvidia-container-toolkit.x86_64 0:1.11.0-1 will be updated
---> Package nvidia-container-toolkit.x86_64 0:1.12.0-0.1.rc.3 will be an update
--> Processing Dependency: nvidia-container-toolkit-base = 1.12.0-0.1.rc.3 for package: nvidia-container-toolkit-1.12.0-0.1.rc.3.x86_64
--> Processing Dependency: libnvidia-container-tools >= 1.12.0-0.1.rc.3 for package: nvidia-container-toolkit-1.12.0-0.1.rc.3.x86_64
--> Running transaction check
---> Package libnvidia-container-tools.x86_64 0:1.11.0-1 will be updated
---> Package libnvidia-container-tools.x86_64 0:1.12.0-0.1.rc.3 will be an update
--> Processing Dependency: libnvidia-container1(x86-64) >= 1.12.0-0.1.rc.3 for package: libnvidia-container-tools-1.12.0-0.1.rc.3.x86_64
---> Package nvidia-container-toolkit-base.x86_64 0:1.11.0-1 will be updated
---> Package nvidia-container-toolkit-base.x86_64 0:1.12.0-0.1.rc.3 will be an update
--> Running transaction check
---> Package libnvidia-container1.x86_64 0:1.11.0-1 will be updated
---> Package libnvidia-container1.x86_64 0:1.12.0-0.1.rc.3 will be an update
--> Finished Dependency ResolutionDependencies Resolved=================================================================================================================================================================================Package Arch Version Repository Size
=================================================================================================================================================================================
Updating:nvidia-container-toolkit x86_64 1.12.0-0.1.rc.3 libnvidia-container-experimental 797 k
Updating for dependencies:libnvidia-container-tools x86_64 1.12.0-0.1.rc.3 libnvidia-container-experimental 50 klibnvidia-container1 x86_64 1.12.0-0.1.rc.3 libnvidia-container-experimental 1.0 Mnvidia-container-toolkit-base x86_64 1.12.0-0.1.rc.3 libnvidia-container-experimental 3.4 MTransaction Summary
=================================================================================================================================================================================
Upgrade 1 Package (+3 Dependent packages)Total download size: 5.2 M
Downloading packages:
Delta RPMs disabled because /usr/bin/applydeltarpm not installed.
(1/4): libnvidia-container-tools-1.12.0-0.1.rc.3.x86_64.rpm | 50 kB 00:00:00
(2/4): nvidia-container-toolkit-1.12.0-0.1.rc.3.x86_64.rpm | 797 kB 00:00:00
(3/4): libnvidia-container1-1.12.0-0.1.rc.3.x86_64.rpm | 1.0 MB 00:00:02
(4/4): nvidia-container-toolkit-base-1.12.0-0.1.rc.3.x86_64.rpm | 3.4 MB 00:00:00
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Total 2.0 MB/s | 5.2 MB 00:00:02
Running transaction check
Running transaction test
Transaction test succeeded
Running transactionUpdating : nvidia-container-toolkit-base-1.12.0-0.1.rc.3.x86_64 1/8 Updating : libnvidia-container1-1.12.0-0.1.rc.3.x86_64 2/8 Updating : libnvidia-container-tools-1.12.0-0.1.rc.3.x86_64 3/8 Updating : nvidia-container-toolkit-1.12.0-0.1.rc.3.x86_64 4/8 Cleanup : nvidia-container-toolkit-1.11.0-1.x86_64 5/8 Cleanup : libnvidia-container-tools-1.11.0-1.x86_64 6/8 Cleanup : libnvidia-container1-1.11.0-1.x86_64 7/8 Cleanup : nvidia-container-toolkit-base-1.11.0-1.x86_64 8/8 Verifying : libnvidia-container1-1.12.0-0.1.rc.3.x86_64 1/8 Verifying : nvidia-container-toolkit-base-1.12.0-0.1.rc.3.x86_64 2/8 Verifying : libnvidia-container-tools-1.12.0-0.1.rc.3.x86_64 3/8 Verifying : nvidia-container-toolkit-1.12.0-0.1.rc.3.x86_64 4/8 Verifying : libnvidia-container-tools-1.11.0-1.x86_64 5/8 Verifying : nvidia-container-toolkit-base-1.11.0-1.x86_64 6/8 Verifying : nvidia-container-toolkit-1.11.0-1.x86_64 7/8 Verifying : libnvidia-container1-1.11.0-1.x86_64 8/8 Updated:nvidia-container-toolkit.x86_64 0:1.12.0-0.1.rc.3 Dependency Updated:libnvidia-container-tools.x86_64 0:1.12.0-0.1.rc.3 libnvidia-container1.x86_64 0:1.12.0-0.1.rc.3 nvidia-container-toolkit-base.x86_64 0:1.12.0-0.1.rc.3 Complete!
[root@bj ~]# systemctl restart docker
6. 测试docker容调用GPU服务
root@hk-MZ32-AR0-00:~# docker run --rm --gpus all 97cca2bac989 nvidia-smi
Sat Feb 11 07:13:48 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.106.00 Driver Version: 460.106.00 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| 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 T4 Off | 00000000:04:00.0 Off | 0 |
| N/A 47C P0 27W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 Tesla T4 Off | 00000000:06:00.0 Off | 0 |
| N/A 43C P0 28W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 Tesla T4 Off | 00000000:0D:00.0 Off | 0 |
| N/A 49C P0 28W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 Tesla T4 Off | 00000000:0F:00.0 Off | 0 |
| N/A 45C P0 26W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 4 Tesla T4 Off | 00000000:17:00.0 Off | 0 |
| N/A 48C P0 27W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 5 Tesla T4 Off | 00000000:19:00.0 Off | 0 |
| N/A 49C P0 28W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 6 Tesla T4 Off | 00000000:21:00.0 Off | 0 |
| N/A 45C P0 26W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 7 Tesla T4 Off | 00000000:23:00.0 Off | 0 |
| N/A 45C P0 28W / 70W | 0MiB / 15109MiB | 5% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------++-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
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