NVIDIA Driver and CUDA Installation on Ubuntu Linux¶
In this article
This instructional guide details the procedure for installing NVIDIA graphics card drivers and CUDA on the subsequent operating systems: Ubuntu 22.04, Ubuntu 24.04.
Attention
For proper operation of Tesla series graphics cards (e.g., NVIDIA Tesla T4), ensure that the server's BIOS has the parameter 'above 4G decoding' or 'large/64bit BARs' or 'Above 4G MMIO BIOS assignment' enabled.
System Preparation¶
-
Update the system:
-
For RTX 4xxx, 5xxx series, A100, and H100 on Ubuntu 22.04, you need to update the kernel version. You can also update the kernel version for older graphics cards:
Installing Nvidia Drivers and CUDA¶
-
Install the gcc compiler, necessary for compiling CUDA:
-
Download and install drivers and CUDA. For Ubuntu 24.04, replace
ubuntu2204
withubuntu2404
in the path ofwget
: -
Set environment variables for your frameworks and applications to detect CUDA in your
.bashrc
:echo 'export PATH="/sbin:/bin:/usr/sbin:/usr/bin:${PATH}:/usr/local/cuda/bin"' >> ~/.bashrc echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64\${LD_LIBRARY_PATH:+:\${LD_LIBRARY_PATH}}' >> ~/.bashrc source ~/.bashrc
Attention
You must run these commands for all users who need to use CUDA.
-
Check the installation of drivers on your video card:
You should get output similar to this:
user@48567:~$ nvidia-smi Fri May 10 15:58:17 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 550.54.15 Driver Version: 550.54.15 CUDA Version: 12.4 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA RTX A4000 Off | 00000000:07:00.0 Off | Off | | 41% 31C P8 15W / 140W | 3MiB / 16376MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | No running processes found | +-----------------------------------------------------------------------------------------+
Attention
If you received a message like
modprobe: ERROR: could not insert 'nvidia': Device or resource busy
during installation, you need to remove thenouveau
kernel module and enable the use ofnvidia
modules.Note
You can find the latest instructions for installing Nvidia GPU drivers on Ubuntu here.
-
Check the CUDA installation:
After a successful installation, you should get output similar to this:
Attention
If you encounter an error like Failed to initialize NVML: Driver/library version mismatch after installation, you need to re-initialize the Nvidia kernel modules by removing them and running nvidia-smi
again.
Installing NVIDIA modules for Docker¶
If you're using Docker containers, don't forget to install the nvidia-docker2
package:
One-Click Installation of Drivers and CUDA¶
You can use this script for automatic installation of drivers and CUDA:
#!/bin/bash
#Check Ubuntu 25.04 and exit
if lsb_release -a | grep -q "25.04"; then
echo "Detected Ubuntu 25.04. NVIDIA do not support official CUDA for non-LTS release. Use Ubuntu 24.04 or 22.04 instead!"
exit
fi
# Update and upgrade the system using apt
sudo apt update
sudo apt upgrade -y
#Check Ubuntu 22.04 and update kernel
lsb_release=$(lsb_release -a | grep "22.04")
if [[ -n "$lsb_release" ]]; then
sudo apt install -y linux-generic-hwe-22.04
fi
# Install GCC compiler for CUDA install
sudo apt install gcc -y
# Get the release version of Ubuntu
RELEASE_VERSION=$(lsb_release -rs | sed 's/\([0-9]\+\)\.\([0-9]\+\)/\1\2/')
# Download and install CUDA package for Ubuntu and Nvidia drivers
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${RELEASE_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
# Update and upgrade the system again to ensure all packages are installed correctly
sudo apt update
sudo apt install cuda -y
sudo apt install cuda-toolkit -y
# Add PATH and LD_LIBRARY_PATH environment variables for CUDA in .bashrc file
echo 'export PATH="/sbin:/bin:/usr/sbin:/usr/bin:${PATH}:/usr/local/cuda/bin"' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64\${LD_LIBRARY_PATH:+:\${LD_LIBRARY_PATH}}' >> ~/.bashrc
source ~/.bashrc
#Initialize kernel modules without reboot
sudo rmmod -f nouveau
sudo nvidia-smi
nvcc -V
#Installing Docker binding for Nvidia
if command -v docker &> /dev/null; then
if lsb_release -a | grep -q "22.04"; then
echo "Detected Ubuntu 22.04. Installing nvidia-docker2..."
sudo apt install -y nvidia-docker2
sudo systemctl restart docker
fi
if lsb_release -a | grep -q "24.04"; then
echo "Detected Ubuntu 24.04. Installing nvidia-container-toolkit..."
sudo apt install -y nvidia-container-toolkit
sudo systemctl restart docker
fi
else
echo "Docker is not installed."
fi
Some of the content on this page was created or translated using AI.