IX device plugin for Kubernetes

Table of Contents

• About
• Prerequisites
• Building the IX device plugin
• Configuring the IX device plugin
• Enabling GPU Support in Kubernetes
• Running GPU Jobs
• Split GPU Board to Multiple GPU Devices
• Shared Access to GPUs

About

The IX device plugin for Kubernetes is a Daemonset that allows you to automatically:

• Expose the number of GPUs on each nodes of your cluster
• Keep track of the health of your GPUs
• Run GPU enabled containers in your Kubernetes cluster.

Prerequisites

The list of prerequisites for running the IX device plugin is described below:

• Iluvatar driver and software stack >= v1.1.0
• Kubernetes version >= 1.10

Building the IX device plugin

make all

This will build the ix-device-plugin binary and ix-device-plugin image, see logging for more details.

Configuring the IX device plugin

The IX device plugin has a number of options that can be configured for it. These options can be configured via a config file when launching the device plugin. Here we explain what each of these options are and how to configure them in configmap.

# ix-config.yaml
apiVersion: v1
kind: ConfigMap
data:
ix-config: |-
    flags:
      splitboard: false
    sharing:
      timeSlicing:
          replicas: 4 

metadata:
  name: ix-config
  namespace: kube-system

kubectl create -f ix-config.yaml

Field	Type	Description
flags.splitboard	boolean	Split GPU devices in every board(eg.BI-V150) if splitboard is true
sharing.timeSlicing.replicas	integer	Specifies the number of GPU time-slicing ​​replicas for shared access

Enabling GPU Support in Kubernetes

Once you have configured the options above on all the GPU nodes in your cluster, you can enable GPU support by deploying the following Daemonset:

# ix-device-plugin.yaml
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: iluvatar-device-plugin
  namespace: kube-system
  labels:
    app.kubernetes.io/name: iluvatar-device-plugin
spec:
  selector:
    matchLabels:
      app.kubernetes.io/name: iluvatar-device-plugin
  template:
    metadata:
      annotations:
        scheduler.alpha.kubernetes.io/critical-pod: ""
      labels:
        app.kubernetes.io/name: iluvatar-device-plugin
    spec:
      priorityClassName: "system-node-critical"
      securityContext:
        null
      containers:
        - name: iluvatar-device-plugin
          securityContext:
            capabilities:
              drop:
              - ALL
            privileged: true
          image: "ix-device-plugin:4.3.0"
          imagePullPolicy: IfNotPresent
          livenessProbe:
            exec:
              command:
              - ls
              - /var/lib/kubelet/device-plugins/iluvatar-gpu.sock
            periodSeconds: 5
          startupProbe:
            exec:
              command:
              - ls
              - /var/lib/kubelet/device-plugins/iluvatar-gpu.sock
            periodSeconds: 5
          resources:
            {}
          volumeMounts:
            - mountPath: /var/lib/kubelet/device-plugins
              name: device-plugin
            - mountPath: /run/udev
              name: udev-ctl
              readOnly: true
            - mountPath: /sys
              name: sys
              readOnly: true
            - mountPath: /dev
              name: dev
            - name: ixc
              mountPath: /ixconfig
      volumes:
        - hostPath:
            path: /var/lib/kubelet/device-plugins
          name: device-plugin
        - hostPath:
            path: /run/udev
          name: udev-ctl
        - hostPath:
            path: /sys
          name: sys
        - hostPath:
            path: /etc/udev/
          name: udev-etc
        - hostPath:
            path: /dev
          name: dev
        - name: ixc
          configMap:
              name: ix-config

kubectl create -f ix-device-plugin.yaml

Running GPU Jobs

GPU can be exposed to a pod by adding iluvatar.com/gpu to the pod definition, and you can restrict the GPU resource by adding resources.limits to the pod definition.

$ cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: Pod
metadata:
  name: corex-example
spec:
  containers:
  - name: corex-example
    image: corex:4.0.0
    command: ["/usr/local/corex/bin/ixsmi"]
    args: ["-l"]
    resources:
      limits:
        iluvatar.com/gpu: 1 # requesting 1 GPUs
EOF

kubectl logs corex-example
+-----------------------------------------------------------------------------+
|  IX-ML: 4.0.0       Driver Version: 4.1.0       CUDA Version: N/A           |
|-------------------------------+----------------------+----------------------|
| GPU  Name                     | Bus-Id               | Clock-SM  Clock-Mem  |
| Fan  Temp  Perf  Pwr:Usage/Cap|      Memory-Usage    | GPU-Util  Compute M. |
|===============================+======================+======================|
| 0    Iluvatar BI-V150S        | 00000000:8A:00.0     | 500MHz    1600MHz    |
| 0%   33C   P0    N/A / N/A    | 114MiB / 32768MiB    | 0%        Default    |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU        PID      Process name                                Usage(MiB) |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

Split GPU Board to Multiple GPU Devices

The IX device plugin allows splitting one GPU board into multiple GPU Devices through a set of extended options in its configuration file.

With SplitBoard

The extended options for splitting board can be seen below:

flags:
    splitboard: false

That is, flags.splitboard, a boolean flag can now be specified. If this flag is set to true, the plugin will split the GPU board into multiple GPUs and kubelet will advertise multiple iluvatar.com/gpu resources to Kubernetes instead of 1 for one GPU board. Otherwise, the plugin will advertise only 1 iluvatar.com/gpu resource for one GPU board.

For example:

flags:
    splitboard: true

If this configuration were applied to a node with 1 GPUs(eg. Bi-V150, which has 2 GPU chips on it) on it, the plugin would now advertise 2 iluvatar.com/gpu resources to Kubernetes instead of 1.

$ kubectl describe node
...
Capacity:
  iluvatar.com/gpu: 2
...

Shared Access to GPUs

The IX device plugin allows oversubscription of GPUs through a set of extended options in its configuration file.

With Time-Slicing

The extended options for sharing using time-slicing can be seen below:

sharing:
    timeSlicing:
        replicas: <num-replicas>
    ...

That is, sharing.timeSlicing.replicas, a number of replicas can now be specified. These replicas represent the number of shared accesses that will be granted for a GPU.

For example:

flags:
    splitboard: false
sharing:
    timeSlicing:
        replicas: 4

If this configuration were applied to a node with 2 GPUs on it, the plugin would now advertise 8 iluvatar.com/gpu resources to Kubernetes instead of 2.

$ kubectl describe node
...
Capacity:
  iluvatar.com/gpu: 8
...