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gpu-provider-configuration.md

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GPU Provider Configuration

Overview

Sections in this guide cover the installation of the following packages necessary for Akash Provider GPU hosting:

GPU PROVIDERS - ensure that your GPU models exist in this database/JSON file before proceeding. If your GPU models do not yet exist in this file - please first follow the procedure outlined in this GPU Configuration Integration Guide to capture your GPU vendor/model IDs and then allow the Akash core team to populate the JSON file prior to updating your provider.

Install NVIDIA Drivers & Toolkit

NOTE - The steps in this section should be completed on all Kubernetes nodes hosting GPU resources

Prepare Environment

NOTE - reboot the servers following the completion of this step

apt update

DEBIAN_FRONTEND=noninteractive apt -y -o Dpkg::Options::="--force-confdef" -o Dpkg::Options::="--force-confold" dist-upgrade

apt autoremove

Install Latest NVIDIA Drivers

The ubuntu-drivers devices command detects your GPU and determines which version of the NVIDIA drivers is best.

NOTE - the NVIDIA drivers detailed and installed in this section have known compatibility issues with some 6.X lLinux kernels as discussed here. In our experience, when such compatibility issue occur the driver will install with no errors generated but will not functionality properly. If you encounter Linux kernel and NVIDIA driver compatibility issues, consider downgrading the Kernel to the officially supported Ubuntu 22.04 kernel which at the time of this writing is 5.15.0-73

apt install ubuntu-drivers-common

ubuntu-drivers devices

Expected/Example Output

root@node1:~# ubuntu-drivers devices

== /sys/devices/pci0000:00/0000:00:1e.0 ==
modalias : pci:v000010DEd00001EB8sv000010DEsd000012A2bc03sc02i00
vendor   : NVIDIA Corporation
model    : TU104GL [Tesla T4]
driver   : nvidia-driver-450-server - distro non-free
driver   : nvidia-driver-418-server - distro non-free
driver   : nvidia-driver-470-server - distro non-free
driver   : nvidia-driver-515 - distro non-free
driver   : nvidia-driver-510 - distro non-free
driver   : nvidia-driver-525-server - distro non-free
driver   : nvidia-driver-525 - distro non-free recommended
driver   : nvidia-driver-515-server - distro non-free
driver   : nvidia-driver-470 - distro non-free
driver   : xserver-xorg-video-nouveau - distro free builtin

Driver Install Based on Output

Run either ubuntu-drivers autoinstall or apt install nvidia-driver-525 (driver names may be different in your environment).

The autoinnstall option installs the recommended version and is appropriate in most instances.

The apt install <driver-name>alternatively allows the install of preferred driver instead of the recommended version.

ubuntu-drivers autoinstall

Install the NVIDIA CUDA Toolkit

NOTE - The steps in this sub-section should be completed on all Kubernetes nodes hosting GPU resources

distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/libnvidia-container/gpgkey | apt-key add -
curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | tee /etc/apt/sources.list.d/libnvidia-container.list

apt-get update
apt-get install -y nvidia-cuda-toolkit nvidia-container-toolkit nvidia-container-runtime

For non-PCIe, e.g. SXM* GPUs

In some circumstances it has been found that the CUDA Drivers Fabric Manager needs to be installed on worker nodes hosting GPU resources (typically, non-PCIe GPU configurations such as those using SXM form factors).

Replace 525 with your nvidia driver version installed in the previous steps

apt-get install cuda-drivers-fabricmanager-525

Reference

Additional References for Node Configurations

NOTE - references are for additional info only. No actions are necessary and the Kubernetes nodes should be all set to proceed to next step based on configurations enacted in prior steps on this doc.

NVIDIA Runtime Configuration

Worker nodes

NOTE - The steps in this sub-section should be completed on all Kubernetes nodes hosting GPU resources

Update the nvidia-container-runtime config in order to prevent NVIDIA_VISIBLE_DEVICES=all abuse where tenants could access more GPU's than they requested.

NOTE - This will only work with nvdp/nvidia-device-plugin helm chart installed with --set deviceListStrategy=volume-mounts (you'll get there in the next steps)

Make sure the config file /etc/nvidia-container-runtime/config.toml contains these line uncommmented and set to these values:

accept-nvidia-visible-devices-as-volume-mounts = true
accept-nvidia-visible-devices-envvar-when-unprivileged = false

NOTE - /etc/nvidia-container-runtime/config.toml is part of nvidia-container-toolkit-base package; so it won't override the customer-set parameters there since it is part of the /var/lib/dpkg/info/nvidia-container-toolkit-base.conffiles

Kubespray

NOTE - the steps in this sub-section should be completed on the Kubespray host only

NOTE - skip this sub-section if these steps were completed during your Kubernetes build process

In this step we add the NVIDIA runtime confguration into the Kubespray inventory. The runtime will be applied to necessary Kubernetes hosts when Kubespray builds the cluster in the subsequent step.

Create NVIDIA Runtime File for Kubespray Use

cat > ~/kubespray/inventory/akash/group_vars/all/akash.yml <<'EOF'
containerd_additional_runtimes:
  - name: nvidia
    type: "io.containerd.runc.v2"
    engine: ""
    root: ""
    options:
      BinaryName: '/usr/bin/nvidia-container-runtime'
EOF

Kubespray the Kubernetes Cluster

cd ~/kubespray

source venv/bin/activate

ansible-playbook -i inventory/akash/hosts.yaml -b -v --private-key=~/.ssh/id_rsa cluster.yml