Using cloud GPUs/fr: Difference between revisions
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Revision as of 15:50, 20 April 2020
This guide describes how to allocate GPU resources to a virtual machine (VM), installing the necessary drivers and checking whether the GPU can be used.
Supported flavors
To use a GPU within a VM, the instance needs to be deployed on one of the flavors listed below. The GPU will be available to the operating system via the PCI bus.
- g2-c24-112gb-500
- g1-c14-56gb-500
- g1-c14-56gb
Preparing a Debian 10 instance
To use the GPU via the PCI bus, the proprietary NVIDIA drivers are required. Due to Debian's policy, the drivers are available from the non-free pool only.
Enable the non-free pool
Log in using ssh and add the lines below to /etc/apt/sources.list, if they are not already there.
deb http://deb.debian.org/debian buster main contrib non-free deb http://security.debian.org/ buster/updates main contrib non-free deb http://deb.debian.org/debian buster-updates main contrib non-free
Installer le pilote NVIDIA
The following command:
- updates the
apt
cache, so thatapt
will be aware of the new software pool sections, - updates the OS to the latest software versions, and
- installs kernel headers, an NVIDIA driver, and
pciutils
, which will be required to list the devices connected to the PCI bus.
root@gpu2:~# apt-get update && apt-get -y dist-upgrade && apt-get -y install pciutils linux-headers-`uname -r` linux-headers-amd64 nvidia-driver
If this command finishes successfully, the NVIDIA driver will have been compiled and loaded.
- Check if the GPU is exposed on the PCI bus
root@gpu2:~# lspci -vk [...] 00:05.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1) Subsystem: NVIDIA Corporation GK210GL [Tesla K80] Physical Slot: 5 Flags: bus master, fast devsel, latency 0, IRQ 11 Memory at fd000000 (32-bit, non-prefetchable) [size=16M] Memory at 1000000000 (64-bit, prefetchable) [size=16G] Memory at 1400000000 (64-bit, prefetchable) [size=32M] Capabilities: [60] Power Management version 3 Capabilities: [68] MSI: Enable- Count=1/1 Maskable- 64bit+ Capabilities: [78] Express Endpoint, MSI 00 Kernel driver in use: nvidia Kernel modules: nvidia [...]
- Check that the
nvidia
kernel module is loaded
root@gpu2:~# lsmod | grep nvidia nvidia 17936384 0 nvidia_drm 16384 0
- Start
nvidia-persistenced
, which will create the necessary device files and make the GPU accessible in user space.
root@gpu2:~# service nvidia-persistenced restart root@gpu2:~# ls -al /dev/nvidia* crw-rw-rw- 1 root root 195, 0 Mar 6 18:55 /dev/nvidia0 crw-rw-rw- 1 root root 195, 255 Mar 6 18:55 /dev/nvidiactl crw-rw-rw- 1 root root 195, 254 Mar 6 18:55 /dev/nvidia-modeset
Le GPU est maintenant disponible dans l'espace de l'utilisateur.
Préparer une instance CentOS 7
NVIDIA provides repositories for various distributions, therefore the required software can be installed and maintained via these repositories.
To compile the module sources from the NVIDIA repository, it is necessary to install dkms
.
This will automatically build the modules on kernel updates, and therefore ensures that the GPU is still working after any update of the OS.
dkms
is provided in the EPEL repository.
Kernel headers and the kernel source need to be installed before the NVIDIA driver can be set up.
Enable the EPEL repository and install needed software
[root@gpu-centos centos]# yum -y update && reboot yum -y install epel-release && yum -y install dkms kernel-devel-$(uname -r) kernel-headers-$(uname -r)
Installer le dépôt NVIDIA et installer le paquet du pilote
Installez le dépôt yum
.
[root@gpu-centos centos]# yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo yum install -y cuda-drivers
NVIDIA uses its own GPG key to sign its packages. yum
will ask to autoimport it. Reply "y" for "yes" when prompted.
Retrieving key from http://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/7fa2af80.pub Importing GPG key 0x7FA2AF80: Userid : "cudatools <cudatools@nvidia.com>" Fingerprint: ae09 fe4b bd22 3a84 b2cc fce3 f60f 4b3d 7fa2 af80 From : http://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/7fa2af80.pub Is this ok [y/N]: y
After installation, reboot the VM to properly load the module and create the NVIDIA device files.
[root@gpu-centos ~]# ls -al /dev/nvidia* crw-rw-rw-. 1 root root 195, 0 Mar 10 20:35 /dev/nvidia0 crw-rw-rw-. 1 root root 195, 255 Mar 10 20:35 /dev/nvidiactl crw-rw-rw-. 1 root root 195, 254 Mar 10 20:35 /dev/nvidia-modeset crw-rw-rw-. 1 root root 241, 0 Mar 10 20:35 /dev/nvidia-uvm crw-rw-rw-. 1 root root 241, 1 Mar 10 20:35 /dev/nvidia-uvm-tools
The GPU is now accessible via any user space tool.