Please refer to the Linux Integration Services documentation for more details. Please note that LIS is applicable to Red Hat Enterprise Linux, CentOS, and the Oracle Linux Red Hat Compatible Kernel 5.2-5.11, 6.0-6.10, and 7.0-7.7. If all GPU devices are listed as expected (and documented above), installing LIS is not required. Check if LIS is required by verifying the results of lspci. Install the latest Linux Integration Services for Hyper-V and Azure. sudo yum install kernel kernel-tools kernel-headers kernel-devel If you choose not to update the kernel, ensure that the versions of kernel-devel and dkms are appropriate for your kernel. We recommend that you periodically update CUDA drivers after deployment. Reboot the VM and proceed to verify the installation. The installation can take several minutes. Visit the NVIDIA Download Center or the NVIDIA CUDA Resources page for the full path specific to each version. Replace the path specific to the version you plan to use. The example below shows the CUDA package path for Ubuntu 20.04. ![]() NVIDIA vGPU 14.1, driver branch R510(.exe) NVIDIA vGPU 15.1, driver branch R525(.exe) Ubuntu 16.04 LTS, 18.04 LTS, 20.04 LTS, 22.04 LTS Red Hat Enterprise Linux 7.9 SUSE Linux Enterprise Server 15 SP2+, 15 SP2 The GRID drivers redistributed by Azure do not work on most non-NV series VMs like NC, NCv2, NCv3, ND, and NDv2-series VMs but works on NCasT4v3 series. You do not need to set up a NVIDIA vGPU software license server. These drivers include licensing for GRID Virtual GPU Software in Azure. Install only these GRID drivers on Azure NV VMs, only on the operating systems listed in the following table. Microsoft redistributes NVIDIA GRID driver installers for NV and NVv3-series VMs used as virtual workstations or for virtual applications. The DSVM editions for Ubuntu 16.04 LTS or CentOS 7.4 pre-install NVIDIA CUDA drivers, the CUDA Deep Neural Network Library, and other tools. Ensure that you install or upgrade to the latest supported CUDA drivers for your distribution.Īs an alternative to manual CUDA driver installation on a Linux VM, you can deploy an Azure Data Science Virtual Machine image. Supported distributions and drivers NVIDIA CUDA driversįor the latest CUDA drivers and supported operating systems, visit the NVIDIA website. Manual driver setup information is also available for Windows VMs.įor N-series VM specs, storage capacities, and disk details, see GPU Linux VM sizes. If you choose to install NVIDIA GPU drivers manually, this article provides supported distributions, drivers, and installation and verification steps. See the NVIDIA GPU Driver Extension documentation for supported distributions and deployment steps. ![]() Install or manage the extension using the Azure portal or tools such as the Azure CLI or Azure Resource Manager templates. The NVIDIA GPU Driver Extension installs appropriate NVIDIA CUDA or GRID drivers on an N-series VM. Leave the tty terminal and return to the gui: Ctrl+Alt+F7.įor more detailed instructions, see the NVIDIA CUDA Installation Guide.To take advantage of the GPU capabilities of Azure N-series VMs backed by NVIDIA GPUs, you must install NVIDIA GPU drivers.On Ubuntu 16.04 run sudo service lightdm start, on 18.04 run sudo systemctl start rvice. You can test if the installation was successful by running nvidia-smi.Check the reported driver and CUDA versions. If the installation fails, you will need to check /var/log/nvidia-installer.log or /var/log/cuda-installer.log to find out why. NAME_OF_nįollow the prompts to install the driver and CUDA. ![]() On Ubuntu 16.04 run sudo service lightdm stop, on 18.04 run sudo systemctl stop rvice.įind the runfile you downloaded from step 2 and run it: sudo sh. Upon restart, drop into the tty terminal with Ctrl+Alt+F1 and log in. If you already have nvidia installed, uninstall it: sudo apt-get purge nvidia-* and reboot your machine. Then regenerate the kernel initramfs: sudo update-initramfs -u
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