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GPU服务器安装显卡驱动、CUDA和cuDNN_existing package manager installation of the drive
作者：笔触狂放9 | 2024-05-31 00:07:09
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existing package manager installation of the driver found. it is strongly │
GPU服务器安装cuda和cudnn
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 | +-----------------------------------------------------------------------------+
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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]
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root@hk-MZ32-AR0-00:~# ./cuda_11.0.2_450.51.05_linux.run ┌──────────────────────────────────────────────────────────────────────────────┐ │ Existing package manager installation of the driver found. It is strongly │ │ recommended that you remove this before continuing. │ │ Abort │ │ Continue │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ Up/Down: Move | 'Enter': Select │ └──────────────────────────────────────────────────────────────────────────────┘ # 上下键选择 Continue，按enter，会出现如下画面 ┌──────────────────────────────────────────────────────────────────────────────┐ │ End User License Agreement │ │ -------------------------- │ │ │ │ NVIDIA Software License Agreement and CUDA Supplement to │ │ Software License Agreement. │ │ │ │ │ │ Preface │ │ ------- │ │ │ │ The Software License Agreement in Chapter 1 and the Supplement │ │ in Chapter 2 contain license terms and conditions that govern │ │ the use of NVIDIA software. By accepting this agreement, you │ │ agree to comply with all the terms and conditions applicable │ │ to the product(s) included herein. │ │ │ │ │ │ NVIDIA Driver │ │ │ │ │ │──────────────────────────────────────────────────────────────────────────────│ │ Do you accept the above EULA? (accept/decline/quit): │ │ │ └──────────────────────────────────────────────────────────────────────────────┘ #输入 accept，按enter，回出现如下 ┌──────────────────────────────────────────────────────────────────────────────┐ │ CUDA Installer │ │ - [X] Driver │ │ [X] 450.51.05 │ │ + [X] CUDA Toolkit 11.0 │ │ [X] CUDA Samples 11.0 │ │ [X] CUDA Demo Suite 11.0 │ │ [X] CUDA Documentation 11.0 │ │ Options │ │ Install │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ Up/Down: Move | Left/Right: Expand | 'Enter': Select | 'A': Advanced options │ └──────────────────────────────────────────────────────────────────────────────┘ # 按上下键到 Driver，按空格，取消安装驱动，驱动我们前面已经安装过了。上下键到install，按enter，会出现安装过程 =========== = Summary = =========== Driver: Not Selected Toolkit: Installed in /usr/local/cuda-11.0/ Samples: Installed in /home/hk/, but missing recommended libraries Please make sure that - PATH includes /usr/local/cuda-11.0/bin - LD_LIBRARY_PATH includes /usr/local/cuda-11.0/lib64, or, add /usr/local/cuda-11.0/lib64 to /etc/ld.so.conf and run ldconfig as root To uninstall the CUDA Toolkit, run cuda-uninstaller in /usr/local/cuda-11.0/bin Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-11.0/doc/pdf for detailed information on setting up CUDA. ***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least .00 is required for CUDA 11.0 functionality to work. To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file: sudo <CudaInstaller>.run --silent --driver Logfile is /var/log/cuda-installer.log
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把cuda的命令添加到系统环境变量
root@hk-MZ32-AR0-00:~# export PATH=$PATH:/usr/local/cuda/bin/ >> /etc/profile
root@hk-MZ32-AR0-00:~# source /etc/profile
# 执行nvcc命令即可显示cuda的信息
root@hk-MZ32-AR0-00:~# nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Thu_Jun_11_22:26:38_PDT_2020
Cuda compilation tools, release 11.0, V11.0.194
Build cuda_11.0_bu.TC445_37.28540450_0
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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:~# rz ZMODEM 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
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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
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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/
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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 33 root@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
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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 $(lsb_release -cs) stable"
root@hk-MZ32-AR0-00:~# apt-get -y install docker-ce
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5. 安装nvidia-docker2
5.1 ubuntu系统安装
root@hk-MZ32-AR0-00:~# curl -s -L https://nvidia.github.io/nvidia-docker/$(. /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:~# sed -i 's/18.04/22.04/g' /etc/apt/sources.list.d/nvidia-docker.list 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 docker
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5.2 centos系统安装
[root@bj ~]# sudo yum install -y nvidia-docker2 Loaded plugins: fastestmirror, product-id, search-disabled-repos, subscription-manager This 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 ecb0 From : 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 ecb0 From : 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 ecb0 From : 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 Resolution Dependencies 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 k libnvidia-container1 x86_64 1.11.0-1 libnvidia-container 1.0 M nvidia-container-toolkit x86_64 1.11.0-1 libnvidia-container 780 k nvidia-container-toolkit-base x86_64 1.11.0-1 libnvidia-container 2.5 M Transaction 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 transaction Installing : 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 0:1.11.0-1 Complete!
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- 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-manager This 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 Resolution Dependencies 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 k libnvidia-container1 x86_64 1.12.0-0.1.rc.3 libnvidia-container-experimental 1.0 M nvidia-container-toolkit-base x86_64 1.12.0-0.1.rc.3 libnvidia-container-experimental 3.4 M Transaction 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 transaction Updating : 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
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6. 测试docker容调用GPU服务
root@hk-MZ32-AR0-00:~# docker run --rm --gpus all nvidia/cuda:10.0-base 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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