Using cloud GPUs: Difference between revisions

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<!--T:2-->
This page describes how to  
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.
* 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 [https://arbutus.cloud.computecanada.ca Arbutus Cloud]. Please note that the documentation below only covers the vGPU driver installation. The [https://developer.nvidia.com/cuda-toolkit-archive CUDA toolkit] is not pre-installed but you can install it directly from  NVIDIA or load it from [[Accessing_CVMFS|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 == <!--T:23-->
== Supported flavors ==


<!--T:3-->
<!--T:3-->
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.
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.


<!--T:4-->
<!--T:4-->
* g2-c24-112gb-500
* g1-8gb-c4-22gb
* g1-c14-56gb-500
* g1-16gb-c8-40gb
* g1-c14-56gb


== Preparing a Debian 10 instance == <!--T:5-->
== Preparation of a VM running AlmaLinux 9 ==  


<!--T:24-->
Once the VM is available, make sure to update the OS to the latest available software, including the kernel.
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.
Then, reboot the VM to have the latest kernel running.


===== Enable the non-free pool ===== <!--T:6-->
To have access to the [https://en.wikipedia.org/wiki/Dynamic_Kernel_Module_Support DKMS package], the [https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm EPEL repository] is required.


<!--T:25-->
AlmaLinux 9 has by default a faulty <code>nouveau</code> driver which crashes the kernel as soon as the <code>nvidia</code> driver is mounted.  
Log in using ssh and add the lines below to ''/etc/apt/sources.list'', if they are not already there.
The VM needs a few extra steps to prevent the loading of the nouveau driver when the system boots.


<!--T:7-->
</translate>
<pre>
<pre>
deb http://deb.debian.org/debian buster main contrib non-free
[root@almalinux9]# echo -e "blacklist nouveau\noptions nouveau modeset=0" >/etc/modprobe.d/blacklist-nouveau.conf
deb http://security.debian.org/ buster/updates main contrib non-free
[root@almalinux9]# dracut -fv --omit-drivers nouveau
deb http://deb.debian.org/debian buster-updates main contrib non-free
[root@almalinux9]# dnf -y update && dnf -y install epel-release && reboot
</pre>
</pre>
<translate>


===== Install the NVIDIA driver ===== <!--T:8-->
After the reboot of the VM, the Arbutus vGPU Cloud repository needs to be installed.
 
</translate>
<pre>
[root@almalinux9]# dnf install http://repo.arbutus.cloud.computecanada.ca/pulp/repos/alma9/Packages/a/arbutus-cloud-vgpu-repo-1.0-1.el9.noarch.rpm</pre>
<translate>
 
The next step is to install the vGPU packages, which will install the required driver and user-space tools.
 
</translate>
<pre>
[root@almalinux9]# dnf -y install nvidia-vgpu-gridd.x86_64 nvidia-vgpu-tools.x86_64 nvidia-vgpu-kmod.x86_64
</pre>
<translate>
 
After a successful  installation, <code>nvidia-smi</code> can be used to verify the proper functionality.
 
</translate>
<pre>
[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                                                            |
+-----------------------------------------------------------------------------------------+
</pre>
<translate>
 
== Preparation of a VM running AlmaLinux 8 ==
 
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 [https://en.wikipedia.org/wiki/Dynamic_Kernel_Module_Support DKMS package], the EPEL repository is required.
 
</translate>
<pre>
[root@vgpu almalinux]# dnf -y update && dnf -y install epel-release && reboot
</pre>
<translate>
 
After the reboot of the VM, the Arbutus vGPU Cloud repository needs to be installed.
 
</translate>
<pre>
[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
</pre>
<translate>
 
The next step is to install the vGPU packages, which will install the required driver and user-space tools.
</translate>
<pre>
[root@vgpu almalinux]# dnf -y install nvidia-vgpu-gridd.x86_64 nvidia-vgpu-tools.x86_64 nvidia-vgpu-kmod.x86_64
</pre>
<translate>
 
After a successful  installation, <code>nvidia-smi</code> can be used to verify the proper functionality.
 
</translate>
<pre>
[root@almalinux8]# nvidia-smi
+-----------------------------------------------------------------------------------------+
| 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                                                            |
+-----------------------------------------------------------------------------------------+
</pre>
<translate>
 
== Preparation of a VM running Debian 11 ==
Ensure that the latest packages are installed and the system has been booted with the latest stable kernel, as <b>DKMS</b> will request the latest one available from the Debian repositories.
 
</translate>
<pre>
root@debian11:~# apt-get update && apt-get -y dist-upgrade && reboot
</pre>
<translate>


<!--T:26-->
After a successful reboot, the system should have the latest available kernel running and the repository can be installed, by installing the <code>arbutus-cloud-repo</code> package.
The following command:
This package also contains the gpg key all packages are signed with.
* updates the <code>apt</code> cache, so that <code>apt</code> 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 <code>pciutils</code>, which will be required to list the devices connected to the PCI bus.  


<!--T:9-->
</translate>
<pre>
<pre>
root@gpu2:~# apt-get update && apt-get -y dist-upgrade && apt-get -y install pciutils linux-headers-`uname -r` linux-headers-amd64 nvidia-driver
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
</pre>
</pre>
<translate>


<!--T:27-->
Update the local apt cache and install the vGPU packages:
If this command finishes successfully, the NVIDIA driver will have been compiled and loaded. 


<!--T:10-->
</translate>
* Check if the GPU is exposed on the PCI bus
<pre>
<pre>
root@gpu2:~# lspci -vk
root@debian11:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
[...]
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
[...]
</pre>
</pre>


<!--T:11-->
* Check that the <code>nvidia</code> kernel module is loaded
<pre>
<pre>
root@gpu2:~# lsmod | grep nvidia
root@debian11:~# nvidia-smi
nvidia             17936384 0
Tue Apr 23 18:55:18 2024     
nvidia_drm             16384 0
+-----------------------------------------------------------------------------------------+
| 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                                                            |
+-----------------------------------------------------------------------------------------+
</pre>
</pre>
<translate>


<!--T:12-->
== Preparation of a VM running Debian 12 ==
* Start <code>nvidia-persistenced</code>, which will create the necessary device files and make the GPU accessible in user space.
Ensure that the latest packages are installed and the system has been booted with the latest stable kernel, as <b>DKMS</b> will request the latest one available from the Debian repositories.
 
</translate>
<pre>
<pre>
root@gpu2:~# systemctl restart nvidia-persistenced
root@debian12:~# apt-get update && apt-get -y dist-upgrade && reboot
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
</pre>  
</pre>  
<translate>


<!--T:14-->
After a successful reboot, the system should have the latest available kernel running and the repository can be installed, by installing the <code>arbutus-cloud-repo</code> package.
The GPU is now available within the user space and can be used.
This package also contains the gpg key all packages are signed with.


== Preparing a CentOS 7 instance == <!--T:15-->
</translate>
<pre>
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
</pre>
<translate>


<!--T:28-->
Update the local apt cache and install the vGPU packages:
NVIDIA provides repositories for various distributions, therefore the required software can be installed and maintained via these repositories.


<!--T:16-->
</translate>
To compile the module sources from the NVIDIA repository, it is necessary to install <code>dkms</code>.
<pre>
This will automatically build the modules on kernel updates, and therefore ensures that the GPU is still working after any update of the OS.
root@debian12:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
<code>dkms</code> is provided in the EPEL repository.
</pre>
Kernel headers and the kernel source need to be installed before the NVIDIA driver can be set up.
 
<pre>
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                                                            |
+-----------------------------------------------------------------------------------------+
</pre>
<translate>


===== Enable the EPEL repository and install needed software ===== <!--T:17-->
== Preparation of a VM running Ubuntu 22 ==  
Ensure that the OS is up to date, that all the latest patches are installed, and that the latest stable kernel is running.


<!--T:29-->
</translate>
<pre>
<pre>
[root@gpu-centos centos]# yum -y update && reboot
root@ubuntu22:~# apt-get update && apt-get -y dist-upgrade && reboot
yum -y install epel-release && yum -y install dkms kernel-devel-$(uname -r) kernel-headers-$(uname -r)
</pre>
</pre>
<translate>


===== Add the NVIDIA repository and install the driver package ===== <!--T:18-->
After a successful reboot, the system should have the latest available kernel running.
Now the repository can be installed by installing the <code>arbutus-cloud-repo</code> package.
This package also contains the gpg key all packages are signed with.


<!--T:30-->
</translate>
Install the <code>yum</code> repository:
<pre>
<pre>
[root@gpu-centos centos]# yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo
root@ubuntu22:~# wget http://repo.arbutus.cloud.computecanada.ca/pulp/deb/ubnt22/pool/main/arbutus-cloud-repo_0.1_all.deb
yum install -y cuda-drivers
root@ubuntu22:~# apt-get install ./arbutus-cloud-repo_0.1_all.deb
</pre>
</pre>
<translate>


<!--T:19-->
Update the local apt cache and install the vGPU packages:
NVIDIA uses its own GPG key to sign its packages.  <code>yum</code> will ask to autoimport it.  Reply "y" for "yes" when prompted.
</translate>
<pre>
<pre>
Retrieving key from http://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/7fa2af80.pub
root@ubuntu22:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
Importing GPG key 0x7FA2AF80:
</pre>
  Userid    : "cudatools <cudatools@nvidia.com>"
<translate>
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
If your installation was successful, the vGPU will be accessible and licensed.
Is this ok [y/N]: y
 
</pre>  
</translate>
<pre>
root@ubuntu22:~# 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                                                            |
+-----------------------------------------------------------------------------------------+
</pre>
<translate>
 
== Preparation of a VM running Ubuntu 20 ==
Ensure that the OS is up to date, that all the latest patches are installed, and that the latest stable kernel is running.
 
</translate>
<pre>
root@ubuntu20:~# apt-get update && apt-get -y dist-upgrade && reboot
</pre>
<translate>
 
After a successful reboot, the system should have the latest available kernel running.
Now the repository can be installed by installing the <code>arbutus-cloud-repo</code> package.
This package also contains the gpg key all packages are signed with.
 
</translate>
<pre>
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
</pre>
<translate>


<!--T:21-->
Update the local apt cache and install the vGPU packages:
After installation, reboot the VM to properly load the module and create the NVIDIA device files.
</translate>
<pre>
<pre>
[root@gpu-centos ~]# ls -al /dev/nvidia*
root@ubuntu20:~# apt-get update && apt-get -y install nvidia-vgpu-kmod nvidia-vgpu-tools nvidia-vgpu-gridd
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
</pre>
</pre>
<translate>


<!--T:22-->
If your installation was successful, the vGPU will be accessible and licensed.
The GPU is now accessible via any user space tool.


</translate>
</translate>
<pre>
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                                                            |
+-----------------------------------------------------------------------------------------+
</pre>
[[Category:Cloud]]
[[Category:Cloud]]

Revision as of 18:12, 29 October 2024

Other languages:

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 AlmaLinux 9

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.

AlmaLinux 9 has by default a faulty nouveau driver which crashes the kernel as soon as the nvidia driver is mounted. The VM needs a few extra steps to prevent the loading of the nouveau driver when the system boots. 

[root@almalinux9]# echo -e "blacklist nouveau\noptions nouveau modeset=0" >/etc/modprobe.d/blacklist-nouveau.conf
[root@almalinux9]# dracut -fv --omit-drivers nouveau
[root@almalinux9]# dnf -y update && dnf -y install epel-release && reboot

After the reboot of the VM, the Arbutus vGPU Cloud repository needs to be installed. 

[root@almalinux9]# 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@almalinux9]# 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 AlmaLinux 8

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 vGPU 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 
+-----------------------------------------------------------------------------------------+
| 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 Debian 11

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
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 Debian 12

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 Ubuntu 22

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

Update the local apt cache and install the vGPU packages: 

root@ubuntu22:~# 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@ubuntu22:~# 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 Ubuntu 20

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                                                             |
+-----------------------------------------------------------------------------------------+
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