Using cloud vGPUs
This page describes how to
- allocate virtual GPU (vGPU) resources to a virtual machine (VM),
- install the necessary drivers and
- check whether the vGPU can be used.
Access to repositories as well as to the vGPUs is currently only available within Arbutus Cloud. Please note that the documentation below only covers the vGPU driver installation. The CUDA toolkit is not pre-installed but you can install it directly from NVIDIA or load it from the CVMFS software stack. If you choose to install the toolkit directly from NVIDIA, please ensure that the vGPU driver is not overwritten with the one from the CUDA package.
Supported flavors
To use a vGPU within a VM, the instance needs to be deployed on one of the flavors listed below. The vGPU will be available to the operating system via the PCI bus.
- g1-8gb-c4-22gb
- g1-16gb-c8-40gb
Preparation of a VM running Almalinux8
Once the VM is available, make sure to update the OS to the latest available software, including the kernel. Then, reboot the VM to have the latest kernel running. To have access to the DKMS package, the EPEL repository is required.
[root@vgpu almalinux]# dnf -y update && dnf -y install epel-release && reboot
After the reboot of the VM, the Arbutus Cloud repository needs to be installed.
[root@almalinux8]# dnf install http://repo.arbutus.cloud.computecanada.ca/pulp/repos/alma8/Packages/a/arbutus-cloud-vgpu-repo-1.0-1.el8.noarch.rpm
The next step is to install the vGPU packages, which will install the required driver and user-space tools.
[root@vgpu almalinux]# dnf -y install nvidia-vgpu-gridd.x86_64 nvidia-vgpu-tools.x86_64 nvidia-vgpu-kmod.x86_64
After a successful installation, nvidia-smi can be used to verify the proper functionality.
[root@almalinux8]# nvidia-smi
Tue Apr 23 16:37:31 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 GRID V100D-8C On | 00000000:00:06.0 Off | 0 |
| N/A N/A P0 N/A / N/A | 0MiB / 8192MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Preparation of a VM running Almalinux9
Once the VM is available, make sure to update the OS to the latest available software, including the kernel. Then, reboot the VM to have the latest kernel running. To have access to the DKMS package, the EPEL repository is required.
[root@vgpu almalinux]# dnf -y update && dnf -y install epel-release && reboot
After the reboot of the VM, the Arbutus Cloud repository needs to be installed.
[root@almalinux8]# dnf install http://repo.arbutus.cloud.computecanada.ca/pulp/repos/alma9/Packages/a/arbutus-cloud-vgpu-repo-1.0-1.el9.noarch.rpm
The next step is to install the vGPU packages, which will install the required driver and user-space tools.
[root@vgpu almalinux]# dnf -y install nvidia-vgpu-gridd.x86_64 nvidia-vgpu-tools.x86_64 nvidia-vgpu-kmod.x86_64
After a successful installation, nvidia-smi can be used to verify the proper functionality.
[root@almalinux9]# nvidia-smi
Tue Apr 23 16:37:31 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 GRID V100D-8C On | 00000000:00:06.0 Off | 0 |
| N/A N/A P0 N/A / N/A | 0MiB / 8192MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Preparation of a VM running Debian12
Ensure that the latest packages are installed and the system has been booted with the latest stable kernel, as DKMS will request the latest one available from the Debian repositories.
root@debian12:~# apt-get update && apt-get -y dist-upgrade && reboot
After a successful reboot, the system should have the latest available kernel running and the repository can be installed, by installing the arbutus-cloud-repo package.
This package also contains the gpg key all packages are signed with.
root@debian12:~# wget http://repo.arbutus.cloud.computecanada.ca/pulp/deb/deb12/pool/main/arbutus-cloud-repo_0.1+deb12_all.deb root@debian12:~# apt-get install -y ./arbutus-cloud-repo_0.1+deb12_all.deb
Update the local apt cache and install the vGPU packages:
root@debian12:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
root@debian12:~# nvidia-smi
Tue Apr 23 18:55:18 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 GRID V100D-8C On | 00000000:00:06.0 Off | 0 |
| N/A N/A P0 N/A / N/A | 0MiB / 8192MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Preparation of a VM running Debian11
Ensure that the latest packages are installed and the system has been booted with the latest stable kernel, as DKMS will request the latest one available from the Debian repositories.
root@debian11:~# apt-get update && apt-get -y dist-upgrade && reboot
After a successful reboot, the system should have the latest available kernel running and the repository can be installed, by installing the arbutus-cloud-repo package.
This package also contains the gpg key all packages are signed with.
root@debian11:~# wget http://repo.arbutus.cloud.computecanada.ca/pulp/deb/deb11/pool/main/arbutus-cloud-repo_0.1_all.deb root@debian11:~# apt-get install -y ./arbutus-cloud-repo_0.1_all.deb
Update the local apt cache and install the vGPU packages:
root@debian11:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
root@debian11:~# nvidia-smi
Wed Apr 24 14:37:52 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 GRID V100D-8C On | 00000000:00:06.0 Off | 0 |
| N/A N/A P0 N/A / N/A | 0MiB / 8192MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Preparation of a VM running Ubuntu20
Ensure that the OS is up to date, that all the latest patches are installed, and that the latest stable kernel is running.
root@ubuntu20:~# apt-get update && apt-get -y dist-upgrade && reboot
After a successful reboot, the system should have the latest available kernel running.
Now the repository can be installed by installing the arbutus-cloud-repo package.
This package also contains the gpg key all packages are signed with.
root@ubuntu20:~# wget http://repo.arbutus.cloud.computecanada.ca/pulp/deb/ubnt20/pool/main/arbutus-cloud-repo_0.1ubuntu20_all.deb root@ubuntu20:~# apt-get install ./arbutus-cloud-repo_0.1ubuntu20_all.deb
Update the local apt cache and install the vGPU packages:
root@ubuntu20:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
If your installation was successful, the vGPU will be accessible and licensed.
root@ubuntu20:~# nvidia-smi
Wed Apr 24 14:37:52 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 GRID V100D-8C On | 00000000:00:06.0 Off | 0 |
| N/A N/A P0 N/A / N/A | 0MiB / 8192MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Preparation of a VM running Ubuntu22
Ensure that the OS is up to date, that all the latest patches are installed, and that the latest stable kernel is running.
root@ubuntu22:~# apt-get update && apt-get -y dist-upgrade && reboot
After a successful reboot, the system should have the latest available kernel running.
Now the repository can be installed by installing the arbutus-cloud-repo package.
This package also contains the gpg key all packages are signed with.
root@ubuntu22:~# wget http://repo.arbutus.cloud.computecanada.ca/pulp/deb/ubnt22/pool/main/arbutus-cloud-repo_0.1_all.deb root@ubuntu22:~#apt-get install ./arbutus-cloud-repo_0.1_all.deb
A warning will be displayed since the signature key is added in the post-install stage; this warning can be ignored. Update the local apt cache and install the vGPU packages:
root@ubuntu20:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
If your installation was successful, the vGPU will be accessible and licensed.