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    Elastic GPU Service:Manually install the Tesla driver on a GPU-accelerated compute-optimized Linux instance

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    Elastic GPU Service:Manually install the Tesla driver on a GPU-accelerated compute-optimized Linux instance

    Last Updated:Jan 06, 2026

    For workloads like deep learning, AI, or graphics acceleration in applications (such as OpenGL, Direct3D, and cloud gaming), GPUs provide high-performance computing and smooth graphics rendering only after a Tesla driver is installed. If you did not install a Tesla driver when creating your GPU-accelerated compute-optimized Linux instance, you must install it manually afterward. This document explains how to install the Tesla driver on such Linux instances.

    Note

    If your instance runs Alibaba Cloud Linux 3 and you did not install the Tesla driver during creation, you can also install it using YUM. For more information, see Use YUM to quickly install the NVIDIA Tesla driver on a GPU-accelerated compute-optimized Alibaba Cloud Linux 3 instance.

    Procedure

    This procedure applies to all GPU-accelerated compute-optimized Linux instances. For more information, see GPU-accelerated compute-optimized instance families (gn, ebm, and scc series). You must install a Tesla driver compatible with the instance's operating system.

    Step 1: Download the Tesla driver

    1. Visit the NVIDIA driver download page.

      Note

      For more information about how to install and configure an NVIDIA driver, see NVIDIA CUDA Installation Guide for Linux.

    2. Configure search conditions and click Find to search for a driver that is suitable for your instance.

      Tesla驱动.jpg

      The following table describes the search conditions.

      Condition

      Description

      Example

      • Product type

      • Product series

      • Product family

      Select the product type, series, and family based on the GPU of the GPU-accelerated instance.

      Note

      To view the details of a GPU-accelerated instance, such as its instance ID, instance type, and operating system, see View instance information.

      • Data Center / Tesla

      • A-Series

      • NVIDIA A10

      Operating system

      Select a Linux version based on the image of the instance.

      Linux 64-bit

      CUDA Toolkit version

      Select a CUDA Toolkit version.

      11.4

      Language

      Select a language for the driver.

      Chinese (Simplified)

      GPUs, supported driver versions, and CUDA Toolkit versions for some GPU-accelerated compute-optimized instance types

      Instance type

      gn8v

      gn8is

      gn7e

      gn7i

      gn7

      gn6e

      gn6i

      gn6v

      gn5i

      gn5

      Product type

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Data Center / Tesla

      Product series

      H-Series

      L-Series

      A-Series

      A-Series

      A-Series

      V-Series

      T-Series

      V-Series

      P-Series

      P-Series

      Recommended Tesla driver version

      Version 570.133.20 or later

      Version 450.80.02 or later

      Version 460.73.01 or later

      Version 450.80.02 or later

      Version 410.79 or later

      Recommended CUDA Toolkit version

      CUDA Toolkit 12.4 Update 1

      CUDA Toolkit 11.0 Update 1

      CUDA Toolkit 11.2

      CUDA Toolkit 11.0 Update 1

      CUDA Toolkit 10.1 Update 2

      Note

      • The table above lists GPU information for only some common GPU-accelerated compute-optimized instance types. Instances with the same GPU model use the same GPU information (product type, series, and family). For example, both ebmgn7i and gn7i instances use the NVIDIA A10 GPU, and thus their product type, series, and family are the same.

      • When manually installing a Tesla driver and a CUDA package, ensure the driver and CUDA package versions are compatible. For more information, see CUDA Compatibility.

    3. On the search result page, click View More Versions.

    4. Find the driver version you want to download and click View next to the driver name.

      For example, select Data Center Driver for Linux x64 with driver version 470.161.03 and CUDA Toolkit version 11.4.

    5. On the driver details page, right-click Download and select Copy URL.

      驱动下载.jpg

    6. Connect to your Linux GPU instance.

      For more information, see Connect to a Linux instance using Workbench.

    7. Run the following command to download the driver installation package.

      The driver download URL in the example command is the link you copied in Substep 5. 

      wget https://us.download.nvidia.com/tesla/470.161.03/NVIDIA-Linux-x86_64-470.161.03.run

    Step 2: Install the Tesla driver

    The installation method varies by different operating systems.

    CentOS

    1. Run the following command to check whether the kernel-devel and kernel-headers packages are installed on the GPU-accelerated instance: 

      sudo rpm  -qa | grep $(uname -r)

      • If the output is similar to the following, which includes the version information for the kernel-devel and kernel-headers packages, the packages are already installed. 

        kernel-3.10.0-1062.18.1.el7.x86_64
kernel-devel-3.10.0-1062.18.1.el7.x86_64
kernel-headers-3.10.0-1062.18.1.el7.x86_64

      • If you do not find kernel-devel-* and kernel-headers-* in the output, you must download and install the corresponding versions of the kernel-devel and kernel-headers packages.

        Important

        A mismatch between the kernel and kernel-devel versions causes a driver compilation error during driver installation. Therefore, confirm the version number of kernel-* in the command output before downloading the corresponding version of kernel-devel. In the example output, the kernel version is 3.10.0-1062.18.1.el7.x86_64.

    2. Grant permissions and install the Tesla driver.

      For a Linux 64-bit operating system, we recommend using the .run format of the Tesla driver, such as NVIDIA-Linux-x86_64-xxxx.run. Run the following commands to grant permissions and install the Tesla driver.

      Note

      If you are using other formats of the Tesla driver, such as .deb or .rpm, see the NVIDIA CUDA Installation Guide for Linux for the installation instructions. 

      sudo chmod +x NVIDIA-Linux-x86_64-xxxx.run
      sudo sh NVIDIA-Linux-x86_64-xxxx.run

    3. Run the following command to verify the installation. 

      nvidia-smi

      Output similar to the following indicates a successful installation.

      驱动版本.jpg

    4. (Optional) Enable Persistence Mode by using the NVIDIA Persistence Daemon.

      After the Tesla driver is installed, Persistence Mode is Off by default. The driver is more stable with Persistence Mode enabled. To ensure stable business operations, we recommend that you enable Persistence Mode by using the NVIDIA Persistence Daemon. For more information, see Persistence Daemon on the official NVIDIA website.

      Note

      1. Run the following command to start the NVIDIA Persistence Daemon. 

        sudo nvidia-persistenced --user username 
# Replace username with your username.

      2. Run the following command to check the status of Persistence Mode. 

        nvidia-smi

        Output similar to the following indicates Persistence Mode is On.

        persistence.jpg

    5. (Optional) Configure Persistence Mode to enable on system reboot.

      Persistence Mode is disabled after a system reboot. To automatically enable it on startup, follow these steps.

      The Tesla driver installation package installs NVIDIA's scripts (such as example and installer scripts) to /usr/share/doc/NVIDIA_GLX-1.0/samples/nvidia-persistenced-init.tar.bz2.

      1. Run the following commands to decompress and install the NVIDIA scripts.

        cd  /usr/share/doc/NVIDIA_GLX-1.0/samples/
sudo tar xf nvidia-persistenced-init.tar.bz2
cd  nvidia-persistenced-init
sudo sh install.sh

      2. Run the following command to check if the NVIDIA Persistence Daemon is running correctly. 

        sudo systemctl status nvidia-persistenced

        Output similar to the following indicates the NVIDIA Persistence Daemon is running correctly.

        persistence Daemon.jpg

        Note

        You can adapt the NVIDIA Persistence Daemon installation script to your operating system to ensure it works properly.

      3. Run the following command again to confirm that Persistence Mode is On. 

        nvidia-smi

      4. (Optional) Run the following commands to stop the NVIDIA Persistence Daemon.

        You can disable the NVIDIA Persistence Daemon based on your business requirements. 

        sudo systemctl stop nvidia-persistenced
sudo systemctl disable nvidia-persistenced

    6. (Conditionally required) If your GPU instance belongs to the ebmgn8v, ebmgn7, or ebmgn7e instance family, install the nvidia-fabricmanager service that matches your driver version.

      Important

      • For ebmgn8v, ebmgn7, or ebmgn7e instance families, the GPU will not function without the matching nvidia-fabricmanager service.

      • If your instance does not belong to one of these families, skip this step.

      1. Install the nvidia-fabricmanager service.

        You can install the nvidia-fabricmanager service from a repository or a package file. The following examples are for CentOS 7.x and CentOS 8.x with a driver version of 460.91.03. Replace driver_version with the version number of the driver you downloaded in Step 1: Download the Tesla driver.

        • Source code

          • CentOS 7.x

            driver_version=460.91.03
sudo yum -y install yum-utils
sudo yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo
sudo yum install -y nvidia-fabric-manager-${driver_version}-1

          • CentOS 8.x

            driver_version=460.91.03
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
distribution=rhel8
ARCH=$( /bin/arch )
sudo dnf config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$distribution/${ARCH}/cuda-$distribution.repo
sudo dnf module enable -y nvidia-driver:${driver_version_main}
sudo dnf install -y nvidia-fabric-manager-0:${driver_version}-1

        • Installation package

          • CentOS 7.x

            driver_version=460.91.03
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/nvidia-fabric-manager-${driver_version}-1.x86_64.rpm
sudo rpm -ivh nvidia-fabric-manager-${driver_version}-1.x86_64.rpm

          • CentOS 8.x

            driver_version=460.91.03
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/nvidia-fabric-manager-${driver_version}-1.x86_64.rpm
sudo rpm -ivh nvidia-fabric-manager-${driver_version}-1.x86_64.rpm

      2. Run the following commands to start nvidia-fabricmanager: 

        sudo systemctl enable nvidia-fabricmanager
sudo systemctl start nvidia-fabricmanager

      3. Run the following command to check if the service was installed successfully.

        systemctl status nvidia-fabricmanager

        The following output indicates a successful installation.

        Dingtalk_20240910143221.jpg

    Ubuntu and other operating systems

    1. Grant permissions and install the Tesla driver.

      For a Linux 64-bit operating system, we recommend using the .run format of the Tesla driver, such as NVIDIA-Linux-x86_64-xxxx.run. Run the following commands to grant permissions and install the Tesla driver.

      Note

      If you are using other formats of the Tesla driver, such as .deb or .rpm, see the NVIDIA CUDA Installation Guide for Linux for the installation instructions. 

      sudo chmod +x NVIDIA-Linux-x86_64-xxxx.run
      sudo sh NVIDIA-Linux-x86_64-xxxx.run

    2. Run the following command to verify the installation. 

      nvidia-smi

      Output similar to the following indicates a successful installation.

      驱动版本.jpg

    3. (Optional) Enable Persistence Mode by using the NVIDIA Persistence Daemon.

      After the Tesla driver is installed, Persistence Mode is Off by default. The driver is more stable with Persistence Mode enabled. To ensure stable business operations, we recommend that you enable Persistence Mode by using the NVIDIA Persistence Daemon. For more information, see Persistence Daemon on the official NVIDIA website.

      Note

      1. Run the following command to start the NVIDIA Persistence Daemon. 

        sudo nvidia-persistenced --user username 
# Replace username with your username.

      2. Run the following command to check the status of Persistence Mode. 

        nvidia-smi

        Output similar to the following indicates Persistence Mode is On.

        persistence.jpg

    4. (Optional) Configure Persistence Mode to enable on system reboot.

      Persistence Mode is disabled after a system reboot. To automatically enable it on startup, follow these steps.

      The Tesla driver installation package installs NVIDIA's scripts (such as example and installer scripts) to /usr/share/doc/NVIDIA_GLX-1.0/samples/nvidia-persistenced-init.tar.bz2.

      1. Run the following commands to decompress and install the NVIDIA scripts.

        cd  /usr/share/doc/NVIDIA_GLX-1.0/samples/
sudo tar xf nvidia-persistenced-init.tar.bz2
cd  nvidia-persistenced-init
sudo sh install.sh

      2. Run the following command to check if the NVIDIA Persistence Daemon is running correctly. 

        sudo systemctl status nvidia-persistenced

        Output similar to the following indicates the NVIDIA Persistence Daemon is running correctly.

        persistence Daemon.jpg

        Note

        You can adapt the NVIDIA Persistence Daemon installation script to your operating system to ensure it works properly.

      3. Run the following command again to confirm that Persistence Mode is On. 

        nvidia-smi

      4. (Optional) Run the following commands to stop the NVIDIA Persistence Daemon.

        You can disable the NVIDIA Persistence Daemon based on your business requirements. 

        sudo systemctl stop nvidia-persistenced
sudo systemctl disable nvidia-persistenced

    5. (Conditionally required) If your GPU instance belongs to the ebmgn8v, ebmgn7, or ebmgn7e instance family, install the nvidia-fabricmanager service that matches your driver version.

      Important

      • For ebmgn8v, ebmgn7, or ebmgn7e instance families, the GPU will not function without the matching nvidia-fabricmanager service.

      • If your instance does not belong to one of these families, skip this step.

      1. Install nvidia-fabricmanager.

        You can install nvidia-fabricmanager by using the source code or the installation package. The commands that are required to install nvidia-fabricmanager vary based on the OS. In the following examples, Ubuntu 16.04, Ubuntu 18.04, Ubuntu 20.04, Ubuntu 22.04, and Ubuntu24.04 are used. Replace driver_version with the version of the driver that you downloaded in Step 1: Download the Tesla driver.

        Important

        • On Ubuntu 22.04, the nvidia-fabricmanager service requires a Tesla driver version later than 515.48.07. This example uses driver version 535.154.05.

        • On Ubuntu 24.04, the nvidia-fabricmanager service requires a Tesla driver version later than 550.90.07. This example uses driver version 570.133.20.

        • Source code

          Ubuntu 16.04, Ubuntu 18.04, or Ubuntu 20.04

          driver_version=460.91.03
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
distribution=$(. /etc/os-release;echo $ID$VERSION_ID | sed -e 's/\.//g')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/cuda-$distribution.pin
sudo mv cuda-$distribution.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/3bf863cc.pub
sudo apt-key add 3bf863cc.pub
sudo rm 3bf863cc.pub
sudo echo "deb https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64 /" | tee /etc/apt/sources.list.d/cuda.list
sudo apt-get update
sudo apt-get -y install nvidia-fabricmanager-${driver_version_main}=${driver_version}-*

          Ubuntu 22.04

          driver_version=535.154.05
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
distribution=$(. /etc/os-release;echo $ID$VERSION_ID | sed -e 's/\.//g')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/cuda-$distribution.pin
sudo mv cuda-$distribution.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/3bf863cc.pub
sudo apt-key add 3bf863cc.pub
sudo rm 3bf863cc.pub
sudo echo "deb https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64 /" | tee /etc/apt/sources.list.d/cuda.list
sudo apt-get update
sudo apt-get -y install nvidia-fabricmanager-${driver_version_main}=${driver_version}-*

          Ubuntu 24.04

          driver_version=570.133.20
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
distribution=$(. /etc/os-release;echo $ID$VERSION_ID | sed -e 's/\.//g')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/cuda-$distribution.pin
sudo mv cuda-$distribution.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/3bf863cc.pub
sudo apt-key add 3bf863cc.pub
sudo rm 3bf863cc.pub
sudo echo "deb https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64 /" | tee /etc/apt/sources.list.d/cuda.list
sudo apt-get update
sudo apt-get -y install nvidia-fabricmanager-${driver_version_main}=${driver_version}-*

        • Installation package

          • Ubuntu 16.04

            driver_version=460.91.03
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb
sudo dpkg -i nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb

          • Ubuntu 18.04

            driver_version=460.91.03
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb
sudo dpkg -i nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb

          • Ubuntu 20.04

            driver_version=460.91.03
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb
sudo dpkg -i nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb

          • Ubuntu 22.04

            driver_version=535.154.05 
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb
sudo dpkg -i nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb

          • Ubuntu 24.04

            driver_version=570.133.20 
driver_version_main=$(echo $driver_version | awk -F '.' '{print $1}')
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb
sudo dpkg -i nvidia-fabricmanager-${driver_version_main}_${driver_version}-1_amd64.deb

      2. Run the following commands to start nvidia-fabricmanager: 

        sudo systemctl enable nvidia-fabricmanager
sudo systemctl start nvidia-fabricmanager

      3. Run the following command to check if the service was installed successfully. 

        systemctl status nvidia-fabricmanager

        The following output indicates a successful installation.

        image.png

        Note

        The nvidia-fabricmanager package version must match the Tesla driver version to ensure the GPU functions correctly. On Ubuntu systems, if you install the nvidia-fabricmanager service from an installation package, the apt-daily service may automatically update the package. This can cause a version mismatch between the nvidia-fabricmanager package and the Tesla driver, which can cause the service to fail and make the GPU unusable. For more information about how to resolve this issue, see GPU unavailable due to a version mismatch between nvidia-fabricmanager and the Tesla driver .

    References