denguir/cuda_install.md

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Installation procedure for CUDA / cuDNN / TensorRT

Raw

cuda_install.md

How to install CUDA / cuDNN / TensorRT on Ubuntu

Install NVIDIA drivers

Update & upgrade

sudo apt update && sudo apt upgrade

Remove previous NVIDIA installation

sudo apt autoremove nvidia* --purge

Check Ubuntu devices

ubuntu-drivers devices

You will install the NVIDIA driver whose version is tagged with recommended

Install Ubuntu drivers

sudo ubuntu-drivers autoinstall

Install NVIDIA drivers

My recommended version is 525, adapt to yours

sudo apt install nvidia-driver-525

Reboot & Check

reboot

after restart verify that the following command works

nvidia-smi

Install CUDA drivers

Update & upgrade

sudo apt update && sudo apt upgrade

Install CUDA toolkit

sudo apt install nvidia-cuda-toolkit

Check CUDA install

nvcc --version

Install cuDNN

Download cuDNN .deb file

You can download cuDNN file here. You will need an Nvidia account. Select the cuDNN version for the appropriate CUDA version, which is the version that appears when you run:

nvcc --version

Install cuDNN

sudo apt install ./<filename.deb>
sudo cp /var/cudnn-<something>.gpg /usr/share/keyrings/

My cuDNN version is 8, adapt the following to your version:

sudo apt update
sudo apt install libcudnn8
sudo apt install libcudnn8-dev
sudo apt install libcudnn8-samples

Test CUDA on Pytorch

Create a virtualenv and activate it

sudo apt-get install python3-pip
sudo pip3 install virtualenv 
virtualenv -p py3.10 venv
source venv/bin/activate

Install pytorch

pip3 install torch torchvision torchaudio

Open Python and execute a test

import torch
print(torch.cuda.is_available()) # should be True

t = torch.rand(10, 10).cuda()
print(t.device) # should be CUDA

Install TensorRT

Download tensorrt .deb file

Go to Nvidia webiste here. Select latest TensorRT version that matches your CUDA version and download the DEB file.

sudo apt install ./<filename.deb>
sudo apt update
sudo apt install tensorrt

Verify trtexec

Verify that the trtexec utility is present.

whereis trtexec # should be trtexec: /usr/src/tensorrt/bin/trtexec
/usr/src/tensorrt/bin/trtexec

moodz commented Nov 10, 2023

I used ...
sudo apt install nvidia-driver-470

However when I install the cuda toolkit later in the process the 470 ( recommended ) drivers are uninstalled ?????

The following packages will be REMOVED:
libnvidia-compute-470 libnvidia-compute-470:i386 libnvidia-decode-470
libnvidia-decode-470:i386 libnvidia-encode-470 libnvidia-encode-470:i386
nvidia-compute-utils-470 nvidia-driver-470 nvidia-utils-470
The following NEW packages will be installed:
libcuinj64-11.5 libnvidia-compute-495 libnvidia-compute-510
libnvidia-compute-525 libnvidia-ml-dev nsight-systems nsight-systems-target
nvidia-cuda-dev nvidia-cuda-toolkit nvidia-profiler nvidia-visual-profiler

This breaks my hardware support at runtime ( unsupported HW errors ).

Any clues ?

MilesQLi commented Nov 18, 2023

Is it possible to specify the CUDA version?

cse-repon commented Nov 22, 2023

thanks a lot!

sitexa commented Nov 22, 2023

nvidia-smi
Failed to initialize NVML: Driver/library version mismatch
NVML library version: 545.23

How to fix this problem?
I have previously installed driver-545.23, then removed it , and installed driver-535. Then failed of version mismatch.
Or, how to clean NVML library completely?

cse-repon commented Nov 22, 2023

nvidia-smi
Failed to initialize NVML: Driver/library version mismatch
NVML library version: 545.23
How to fix this problem? I have previously installed driver-545.23, then removed it , and installed driver-535. Then failed of version mismatch. Or, how to clean NVML library completely?

sudo apt-get purge '.nvidia.'
sudo apt remove '.nvidia.'

then followed this gist
and installed this version

sudo apt install nvidia-driver-525

dcerisano commented Nov 23, 2023 •

edited

Loading

If anyone is interested to see a clean install log of these instructions, please see log below.
I followed them to the letter and got the correct result.
Note that this was on a fresh install of Ubuntu Server 22.04, with Gnome desktop and Nvidia drivers installed immediately afterwards.
(I use Ubuntu Server to I can easily congfure my workstation NVME drives in RAID0)

Other than the WARNING: Running pip as the 'root' user these instructions cause, seems fine thanks.

kronos@kronos:~/Downloads$ sudo apt install ./cudnn-local-repo-ubuntu2204-8.9.6.50_1.0-1_amd64.deb 
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
Note, selecting 'cudnn-local-repo-ubuntu2204-8.9.6.50' instead of './cudnn-local-repo-ubuntu2204-8.9.6.50_1.0-1_amd64.deb'
The following NEW packages will be installed:
  cudnn-local-repo-ubuntu2204-8.9.6.50
0 upgraded, 1 newly installed, 0 to remove and 6 not upgraded.
Need to get 0 B/887 MB of archives.
After this operation, 887 MB of additional disk space will be used.
Get:1 /home/kronos/Downloads/cudnn-local-repo-ubuntu2204-8.9.6.50_1.0-1_amd64.deb cudnn-local-repo-ubuntu2204-8.9.6.50 amd64 1.0-1 [887 MB]
Selecting previously unselected package cudnn-local-repo-ubuntu2204-8.9.6.50.
(Reading database ... 190246 files and directories currently installed.)
Preparing to unpack .../cudnn-local-repo-ubuntu2204-8.9.6.50_1.0-1_amd64.deb ...
Unpacking cudnn-local-repo-ubuntu2204-8.9.6.50 (1.0-1) ...
Setting up cudnn-local-repo-ubuntu2204-8.9.6.50 (1.0-1) ...

The public cudnn-local-repo-ubuntu2204-8.9.6.50 GPG key does not appear to be installed.
To install the key, run this command:
sudo cp /var/cudnn-local-repo-ubuntu2204-8.9.6.50/cudnn-local-1998375D-keyring.gpg /usr/share/keyrings/


kronos@kronos:~/Downloads$ cd /var/cudnn-local-repo-ubuntu2204-8.9.6.50/
kronos@kronos:/var/cudnn-local-repo-ubuntu2204-8.9.6.50$ ls
1998375D.pub                      libcudnn8_8.9.6.50-1+cuda12.2_amd64.deb          Local.md5      Packages.gz
cudnn-local-1998375D-keyring.gpg  libcudnn8-dev_8.9.6.50-1+cuda12.2_amd64.deb      Local.md5.gpg  Release
InRelease                         libcudnn8-samples_8.9.6.50-1+cuda12.2_amd64.deb  Packages       Release.gpg
kronos@kronos:/var/cudnn-local-repo-ubuntu2204-8.9.6.50$ sudo cp /var/cudnn-local-repo-ubuntu2204-8.9.6.50/cudnn-local-1998375D-keyring.gpg /usr/share/keyrings/

kronos@kronos:/var/cudnn-local-repo-ubuntu2204-8.9.6.50$ sudo apt update
sudo apt install libcudnn8
sudo apt install libcudnn8-dev
sudo apt install libcudnn8-samples
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Reading package lists... Done
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41 packages can be upgraded. Run 'apt list --upgradable' to see them.
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W: Target DEP-11 (main/dep11/Components-amd64.yml) is configured multiple times in /etc/apt/sources.list.d/google-chrome-unstable.list:3 and /etc/apt/sources.list.d/google-chrome.list:3
W: Target DEP-11 (main/dep11/Components-all.yml) is configured multiple times in /etc/apt/sources.list.d/google-chrome-unstable.list:3 and /etc/apt/sources.list.d/google-chrome.list:3
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W: Target CNF (main/cnf/Commands-amd64) is configured multiple times in /etc/apt/sources.list.d/google-chrome-unstable.list:3 and /etc/apt/sources.list.d/google-chrome.list:3
W: Target CNF (main/cnf/Commands-all) is configured multiple times in /etc/apt/sources.list.d/google-chrome-unstable.list:3 and /etc/apt/sources.list.d/google-chrome.list:3
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
The following NEW packages will be installed:
  libcudnn8
0 upgraded, 1 newly installed, 0 to remove and 41 not upgraded.
Need to get 0 B/444 MB of archives.
After this operation, 1,099 MB of additional disk space will be used.
Get:1 file:/var/cudnn-local-repo-ubuntu2204-8.9.6.50  libcudnn8 8.9.6.50-1+cuda12.2 [444 MB]
Selecting previously unselected package libcudnn8.
(Reading database ... 190262 files and directories currently installed.)
Preparing to unpack .../libcudnn8_8.9.6.50-1+cuda12.2_amd64.deb ...
Unpacking libcudnn8 (8.9.6.50-1+cuda12.2) ...
Setting up libcudnn8 (8.9.6.50-1+cuda12.2) ...

Reading package lists... Done
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Reading state information... Done
The following NEW packages will be installed:
  libcudnn8-dev
0 upgraded, 1 newly installed, 0 to remove and 41 not upgraded.
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Selecting previously unselected package libcudnn8-dev.
(Reading database ... 190279 files and directories currently installed.)
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Unpacking libcudnn8-dev (8.9.6.50-1+cuda12.2) ...
Setting up libcudnn8-dev (8.9.6.50-1+cuda12.2) ...
update-alternatives: using /usr/include/x86_64-linux-gnu/cudnn_v8.h to provide /usr/include/cudnn.h (libcudnn) in auto mode

Reading package lists... Done
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Reading state information... Done
The following NEW packages will be installed:
  libcudnn8-samples
0 upgraded, 1 newly installed, 0 to remove and 41 not upgraded.
Need to get 0 B/1,663 kB of archives.
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Selecting previously unselected package libcudnn8-samples.
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Unpacking libcudnn8-samples (8.9.6.50-1+cuda12.2) ...
Setting up libcudnn8-samples (8.9.6.50-1+cuda12.2) ...

kronos@kronos:/var/cudnn-local-repo-ubuntu2204-8.9.6.50$ cd
kronos@kronos:~$ sudo apt-get install python3-pip
sudo pip3 install virtualenv 
virtualenv -p py3.10 venv
source venv/bin/activate
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
The following additional packages will be installed:
  libexpat1-dev libpython3-dev libpython3.10-dev python3-dev python3-wheel python3.10-dev zlib1g-dev
The following NEW packages will be installed:
  libexpat1-dev libpython3-dev libpython3.10-dev python3-dev python3-pip python3-wheel python3.10-dev zlib1g-dev
0 upgraded, 8 newly installed, 0 to remove and 41 not upgraded.
Need to get 6,952 kB of archives.
After this operation, 30.4 MB of additional disk space will be used.
Do you want to continue? [Y/n] 
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Collecting virtualenv
  Downloading virtualenv-20.24.7-py3-none-any.whl (3.8 MB)
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Collecting distlib<1,>=0.3.7
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Collecting platformdirs<5,>=3.9.1
  Downloading platformdirs-4.0.0-py3-none-any.whl (17 kB)
Installing collected packages: distlib, platformdirs, filelock, virtualenv
Successfully installed distlib-0.3.7 filelock-3.13.1 platformdirs-4.0.0 virtualenv-20.24.7
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
created virtual environment CPython3.10.12.final.0-64 in 293ms
  creator CPython3Posix(dest=/home/kronos/venv, clear=False, no_vcs_ignore=False, global=False)
  seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/home/kronos/.local/share/virtualenv)
    added seed packages: pip==23.3.1, setuptools==68.2.2, wheel==0.41.3
  activators BashActivator,CShellActivator,FishActivator,NushellActivator,PowerShellActivator,PythonActivator
(venv) kronos@kronos:~$ pip3 install torch torchvision torchaudio
Collecting torch
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  Downloading networkx-3.2.1-py3-none-any.whl.metadata (5.2 kB)
Collecting jinja2 (from torch)
  Downloading Jinja2-3.1.2-py3-none-any.whl (133 kB)
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Collecting fsspec (from torch)
  Downloading fsspec-2023.10.0-py3-none-any.whl.metadata (6.8 kB)
Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch)
  Downloading nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)
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Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch)
  Downloading nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)
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Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch)
  Downloading nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)
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Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch)
  Downloading nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)
Collecting nvidia-cublas-cu12==12.1.3.1 (from torch)
  Downloading nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)
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Collecting nvidia-cufft-cu12==11.0.2.54 (from torch)
  Downloading nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)
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Collecting nvidia-curand-cu12==10.3.2.106 (from torch)
  Downloading nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)
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Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch)
  Downloading nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)
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Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch)
  Downloading nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)
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Collecting nvidia-nccl-cu12==2.18.1 (from torch)
  Downloading nvidia_nccl_cu12-2.18.1-py3-none-manylinux1_x86_64.whl (209.8 MB)
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Collecting nvidia-nvtx-cu12==12.1.105 (from torch)
  Downloading nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)
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Collecting triton==2.1.0 (from torch)
  Downloading triton-2.1.0-0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.3 kB)
Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch)
  Downloading nvidia_nvjitlink_cu12-12.3.101-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)
Collecting numpy (from torchvision)
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Collecting requests (from torchvision)
  Downloading requests-2.31.0-py3-none-any.whl.metadata (4.6 kB)
Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)
  Downloading Pillow-10.1.0-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (9.5 kB)
Collecting MarkupSafe>=2.0 (from jinja2->torch)
  Downloading MarkupSafe-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.0 kB)
Collecting charset-normalizer<4,>=2 (from requests->torchvision)
  Downloading charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (33 kB)
Collecting idna<4,>=2.5 (from requests->torchvision)
  Downloading idna-3.4-py3-none-any.whl (61 kB)
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Collecting urllib3<3,>=1.21.1 (from requests->torchvision)
  Downloading urllib3-2.1.0-py3-none-any.whl.metadata (6.4 kB)
Collecting certifi>=2017.4.17 (from requests->torchvision)
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Collecting mpmath>=0.19 (from sympy->torch)
  Downloading mpmath-1.3.0-py3-none-any.whl (536 kB)
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Downloading torch-2.1.1-cp310-cp310-manylinux1_x86_64.whl (670.2 MB)
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Downloading nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)
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Downloading triton-2.1.0-0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89.2 MB)
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Downloading torchvision-0.16.1-cp310-cp310-manylinux1_x86_64.whl (6.8 MB)
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Downloading torchaudio-2.1.1-cp310-cp310-manylinux1_x86_64.whl (3.3 MB)
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Downloading Pillow-10.1.0-cp310-cp310-manylinux_2_28_x86_64.whl (3.6 MB)
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Downloading filelock-3.13.1-py3-none-any.whl (11 kB)
Downloading fsspec-2023.10.0-py3-none-any.whl (166 kB)
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Downloading networkx-3.2.1-py3-none-any.whl (1.6 MB)
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Downloading numpy-1.26.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)
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Downloading requests-2.31.0-py3-none-any.whl (62 kB)
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Downloading typing_extensions-4.8.0-py3-none-any.whl (31 kB)
Downloading certifi-2023.11.17-py3-none-any.whl (162 kB)
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Downloading charset_normalizer-3.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (142 kB)
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Downloading MarkupSafe-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25 kB)
Downloading urllib3-2.1.0-py3-none-any.whl (104 kB)
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Downloading nvidia_nvjitlink_cu12-12.3.101-py3-none-manylinux1_x86_64.whl (20.5 MB)
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Installing collected packages: mpmath, urllib3, typing-extensions, sympy, pillow, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, numpy, networkx, MarkupSafe, idna, fsspec, filelock, charset-normalizer, certifi, triton, requests, nvidia-cusparse-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch, torchvision, torchaudio
Successfully installed MarkupSafe-2.1.3 certifi-2023.11.17 charset-normalizer-3.3.2 filelock-3.13.1 fsspec-2023.10.0 idna-3.4 jinja2-3.1.2 mpmath-1.3.0 networkx-3.2.1 numpy-1.26.2 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.18.1 nvidia-nvjitlink-cu12-12.3.101 nvidia-nvtx-cu12-12.1.105 pillow-10.1.0 requests-2.31.0 sympy-1.12 torch-2.1.1 torchaudio-2.1.1 torchvision-0.16.1 triton-2.1.0 typing-extensions-4.8.0 urllib3-2.1.0

(venv) kronos@kronos:~$ python
Python 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.cuda.is_available()) # should be True
True
>>> 
>>> t = torch.rand(10, 10).cuda()
>>> print(t.device) # should be CUDA
cuda:0
>>>

LouisJULIEN commented Nov 24, 2023

Worked like a charm, thanks!

The only thing I did a bit differently was the gpg key copy. It's now is a subdirectory. Here the command I used:

sudo cp /var/cudnn-local-repo-ubuntu2204-8.9.6.50/cudnn-local-692B6C75-keyring.gpg  /usr/share/keyrings/

LouisJULIEN commented Nov 27, 2023

Some tweaks are required if you're willing to use tensorflow with CUDA:

As of November 2023, you need cudNN v8.6 as stated by the (english) doc. Beware, the latest cudNN version is 8.9. You need to uninstall your previous cudNN to install the right version. Don't forget to uninstall then reinstall libcudnn8 libcudnn8-dev libcudnn8-samplesas well.
To install tensorflow with cuda, use pip install tensorflow[and-cuda]
Check the installation: python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))" . You should see 1 or higher if your setup is right.

ilo-bst commented Dec 22, 2023 •

edited

Loading

Hi, what does <something> stand for in sudo cp /var/cudnn-<something>.gpg /usr/share/keyrings/? My cuDNN file is cudnn-local-repo-ubuntu2204-8.9.7.29_1.0-1_amd64.deb.

ilo-bst commented Dec 22, 2023

Hi, what does <something> stand for in sudo cp /var/cudnn-<something>.gpg /usr/share/keyrings/? My cuDNN file is cudnn-local-repo-ubuntu2204-8.9.7.29_1.0-1_amd64.deb.

I just went to the location /var/cudnn... in my file system and found the appropriate gpg file.

misaelpedro commented Jan 12, 2024

When I was installing cuDNN and ran:

$ sudo apt install ./cudnn-local-repo-ubuntu2204-8.6.0.163_1.0-1_amd64.deb

It returned this at end of output:

The public cudnn-local-repo-ubuntu2204-8.6.0.163 GPG key does not appear to be installed. To install the key, run this command: sudo cp /var/cudnn-local-repo-ubuntu2204-8.6.0.163/<YOURS_KEY>-keyring.gpg /usr/share/keyrings/

Then I ran that command in the end of message and the others ones as it is listed above (libcudnn8, libcudnn8-dev, libcudnn8-samples)

A final tip to check if cuDNN is installed is run :
whereis cudnn.h
It should return : cudnn.h: /usr/include/cudnn.h

aquinovo commented Jan 15, 2024

Thank you. This is very helpful

MaisJamal commented Jan 16, 2024

Thanks, it's very helpful, worked perfectly.

corticalstack commented Jan 23, 2024

@Atlas3DSS Having same issue as you reported. I've purged all nvidia (as I'm aware) and reinstalled nvidia driver, followed by cuda kit, but all I can seem to install is the 11.5 cuda kit version (on Ubuntu 22.04). Any tips to resolve you can share?

tarreislam commented Jan 26, 2024

For anyone having issues on ubuntu 22.04: check this out

NVIDIA/nvidia-docker#1243 (comment)

I switched to bare metal because I thought Esxi was the issue, but after doing this, it worked

flavves commented Apr 8, 2024

Thanks!

Adesojialu commented May 11, 2024

ubuntu-drivers devices
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.

b1shtream commented May 14, 2024 •

edited

Loading

@denguir

trinity@ukiyo:~$ ubuntu-drivers devices
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
== /sys/devices/pci0000:00/0000:00:01.1/0000:01:00.0 ==
modalias : pci:v000010DEd00001F99sv00001025sd00001447bc03sc00i00
vendor   : NVIDIA Corporation
model    : TU117M [GeForce GTX 1650 Mobile / Max-Q]
driver   : nvidia-driver-470-server - distro non-free
driver   : nvidia-driver-525 - third-party non-free
driver   : nvidia-driver-550-open - third-party non-free
driver   : nvidia-driver-535-server - distro non-free
driver   : nvidia-driver-515 - third-party non-free
driver   : nvidia-driver-470 - distro non-free
driver   : nvidia-driver-535-open - distro non-free
driver   : nvidia-driver-550 - third-party non-free recommended
driver   : nvidia-driver-535 - third-party non-free
driver   : nvidia-driver-520 - third-party non-free
driver   : nvidia-driver-535-server-open - distro non-free
driver   : nvidia-driver-545 - third-party non-free
driver   : xserver-xorg-video-nouveau - distro free builtin

trinity@ukiyo:~$ sudo ubuntu-drivers autoinstall
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
Some packages could not be installed. This may mean that you have
requested an impossible situation or if you are using the unstable
distribution that some required packages have not yet been created
or been moved out of Incoming.
The following information may help to resolve the situation:

The following packages have unmet dependencies:
 linux-modules-nvidia-550-generic-hwe-24.04 : Depends: linux-modules-nvidia-550-6.8.0-31-generic (= 6.8.0-31.31) but it is not going to be installed
                                              Depends: nvidia-kernel-common-550 (>= 550.67) but 550.54.15-0ubuntu1 is to be installed
E: Unable to correct problems, you have held broken packages.

after running sudo apt install nvidia-driver-550, the command ubuntu-drivers devices shows:

trinity@ukiyo:~$ ubuntu-drivers devices
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
udevadm hwdb is deprecated. Use systemd-hwdb instead.
== /sys/devices/pci0000:00/0000:00:01.1/0000:01:00.0 ==
modalias : pci:v000010DEd00001F99sv00001025sd00001447bc03sc00i00
vendor   : NVIDIA Corporation
model    : TU117M [GeForce GTX 1650 Mobile / Max-Q]
driver   : nvidia-driver-515 - third-party non-free
driver   : nvidia-driver-535-server - distro non-free
driver   : nvidia-driver-535-open - distro non-free
driver   : nvidia-driver-550 - third-party non-free recommended
driver   : nvidia-driver-520 - third-party non-free
driver   : nvidia-driver-535-server-open - distro non-free
driver   : nvidia-driver-525 - third-party non-free
driver   : nvidia-driver-535 - third-party non-free
driver   : nvidia-driver-470-server - distro non-free
driver   : nvidia-driver-550-open - third-party non-free
driver   : nvidia-driver-545 - third-party non-free
driver   : nvidia-driver-470 - distro non-free
driver   : xserver-xorg-video-nouveau - distro free builtin

shravanvallaban commented May 19, 2024

@chococandy63 I have the same issue, I recently install Ubuntu 24.04 and when I tried install cuda drivers I get the same error.

tmcf22 commented May 27, 2024

This is great! Thank you so much. I have used this as a guideline for installing on multiple computers, maybe 20 times (no joke). Works every time. Much appreciated!

b1shtream commented May 27, 2024

@shravanvallaban I think cuda drivers are not officially supported on Ubuntu 24.04. I mean they are not available on official website. I'm using them on previous Ubuntu versions and they working fine as of now.

chunhanl commented Jun 5, 2024

nice! thank you so much for this

maifeeulasad commented Jun 30, 2024

I followed your instructions and did the following:

sudo apt install nvidia-driver-535

And nvidia-smi had shown me, I have got the correct cuda version (or at least what I was looking for):

Sun Jun 30 17:42:56 2024       
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.183.01             Driver Version: 535.183.01   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+

Abd then I did the following:

sudo apt update && sudo apt upgrade
sudo apt install nvidia-cuda-toolkit

But after doing all this, when I tried looking into the nvcc --version, it gives me the following:

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Thu_Nov_18_09:45:30_PST_2021
Cuda compilation tools, release 11.5, V11.5.119
Build cuda_11.5.r11.5/compiler.30672275_0

Why am I getting this conflict? I want the cuda 12.2 for my nvcc as well. How can I resolve this issue? And upgrade nvcc to use cuda 12.2 as well?

moussahmed commented Aug 4, 2024

I have the same problem @maifeeulasad . Can you help me ?

Muthukamalan commented Aug 6, 2024

I'm using Pop OS, installed successfully, but after sometime. my screen got frozen , every time I went to tty mode and kill gnome session.

please suggest how to resolve. I'm new to linux community

cc: @denguir @maifeeulasad

jt-z commented Sep 9, 2024

Thank you. I have successfully installed it on Linux 22.04 with a 3060GPU, following the official link for cuDNN installation cuDNN 9.4.0 Downloads | NVIDIA Developer.

fordnox commented Oct 8, 2024

This worked for me for Ubuntu 24.04 and GeForce RTX 4060 Ti 16GB after trying multiple versions:

https://gist.github.com/fordnox/538b48ac956341728573786a80e08859

denguir/cuda_install.md

How to install CUDA / cuDNN / TensorRT on Ubuntu

Install NVIDIA drivers

Update & upgrade

Remove previous NVIDIA installation

Check Ubuntu devices

Install Ubuntu drivers

Install NVIDIA drivers

Reboot & Check

Install CUDA drivers

Update & upgrade

Install CUDA toolkit

Check CUDA install

Install cuDNN

Download cuDNN .deb file

Install cuDNN

Test CUDA on Pytorch

Create a virtualenv and activate it

Install pytorch

Open Python and execute a test

Install TensorRT

Download tensorrt .deb file

Verify trtexec

moodz commented Nov 10, 2023

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tmcf22 commented May 27, 2024

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chunhanl commented Jun 5, 2024

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maifeeulasad commented Jun 30, 2024

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moussahmed commented Aug 4, 2024

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Muthukamalan commented Aug 6, 2024

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jt-z commented Sep 9, 2024

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fordnox commented Oct 8, 2024

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