Ubuntu 20.04 LTS, CUDA 11.2.0, NVIDIA 455 and libcudnn 8.0.4

https://askubuntu.com/questions/1077061/how-do-i-install-nvidia-and-cuda-drivers-into-ubuntu

这个方法可以解决很多人在装Pytorch之前解决CUDA依赖的问题,网上很多文章都没有下面这句英语,这是问题关键。

这个问题的核心在下面这句英语:

I don‘t recommend installing the NVIDIA drivers that come with CUDA as they do not contain the dkms drivers that carry over into new kernel upgrades.

If you don‘t have the `graphics-drivers` PPA already setup, add it now to your system and remove any previous NVIDIA drivers.

The Ubuntu repositories now contain the same drivers as the graphics-drivers PPA. So feel free to install the 460.39 drivers.

sudo apt install nvidia-driver-460

Now, download the CUDA 11.2.0 .run file from NVIDIA:

wget https://developer.download.nvidia.com/compute/cuda/11.2.0/local_installers/cuda_11.2.0_460.27.04_linux.run

I like to make it executable:

chmod +x cuda_11.2.0_460.27.04_linux.run

Now install CUDA:

sudo ./cuda_11.2.0_460.27.04_linux.run 

Accept the EULA:

┌──────────────────────────────────────────────────────────────────────────────┐
│  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):                         │
│ accept                                                                            

Unselect the driver by pressing the spacebar while [X] Driver is highlighted:

┌──────────────────────────────────────────────────────────────────────────────┐
│ CUDA Installer                                                               │
│ - [ ] Driver                                                                 │
│      [ ] 460.27.04                                                           │
│ + [X] CUDA Toolkit 11.2                                                      │
│   [X] CUDA Samples 11.2                                                      │
│   [X] CUDA Demo Suite 11.2                                                   │
│   [X] CUDA Documentation 11.2                                             │
│   Options                                                                    │
│   Install                                                                    │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│                                                                              │
│ Up/Down: Move | Left/Right: Expand | ‘Enter‘: Select | ‘A‘: Advanced options │

Then press the down arrow to Install. Press Enter then wait for installation to complete.

After the installation is complete add the following to the bottom of your ~/.profile or add it to the /etc/profile.d/cuda.sh file which you might have to create for all users (global):

# set PATH for cuda 11.2 installation
if [ -d "/usr/local/cuda-11.2/bin/" ]; then
    export PATH=/usr/local/cuda-11.2/bin${PATH:+:${PATH}}
    export LD_LIBRARY_PATH=/usr/local/cuda-11.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
fi

Install libcudnn8

Add the Repo:

NOTEThe 20.04 repo from NVIDIA does not supply libcudnn but the 18.04 repo does and installs just fine into 20.04.

echo "deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda_learn.list

Install the key:

sudo apt-key adv --fetch-keys  http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub

Update the system:

sudo apt update

Install libcudnn 8.0.4:

sudo apt install libcudnn8

I recommend now to reboot the system for the changes to take effect.

After it reboots check the installations:

   $ nvidia-smi
Sat Apr 10 15:13:48 2021       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.39       Driver Version: 460.39       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  GeForce GTX 750 Ti  On   | 00000000:01:00.0  On |                  N/A |
| 42%   50C    P0     2W /  38W |    153MiB /  2000MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      4976      G   /usr/lib/xorg/Xorg                129MiB |
|    0   N/A  N/A      5393      G   compton                             1MiB |
|    0   N/A  N/A    672363      G   ...AAAAAAAAA= --shared-files       17MiB |
+-----------------------------------------------------------------------------+
                                                                        


~$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Mon_Nov_30_19:08:53_PST_2020
Cuda compilation tools, release 11.2, V11.2.67
Build cuda_11.2.r11.2/compiler.29373293


~$ /sbin/ldconfig -N -v $(sed ‘s/:/ /‘ <<< $LD_LIBRARY_PATH) 2>/dev/null | grep libcudnn
    libcudnn_cnn_infer.so.8 -> libcudnn_cnn_infer.so.8.0.4
    libcudnn.so.8 -> libcudnn.so.8.0.4
    libcudnn_adv_train.so.8 -> libcudnn_adv_train.so.8.0.4
    libcudnn_ops_infer.so.8 -> libcudnn_ops_infer.so.8.0.4
    libcudnn_cnn_train.so.8 -> libcudnn_cnn_train.so.8.0.4
    libcudnn_adv_infer.so.8 -> libcudnn_adv_infer.so.8.0.4
    libcudnn_ops_train.so.8 -> libcudnn_ops_train.so.8.0.4
 

Ubuntu 20.04 LTS, CUDA 11.2.0, NVIDIA 455 and libcudnn 8.0.4

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