Table of Contents
The DSA device plugin for Kubernetes supports acceleration using the Intel Data Streaming accelerator(DSA).
The DSA plugin discovers DSA work queues and presents them as a node resources.
The DSA plugin and operator optionally support provisioning of DSA devices and workqueues with the help of accel-config utility through initcontainer.
The following sections detail how to obtain, build, deploy and test the DSA device plugin.
Examples are provided showing how to deploy the plugin either using a DaemonSet or by hand on a per-node basis.
Pre-built images of this component are available on the Docker hub. These images are automatically built and uploaded to the hub from the latest main branch of this repository.
Release tagged images of the components are also available on the Docker hub, tagged with their
release version numbers in the format x.y.z
, corresponding to the branches and releases in this
repository. Thus the easiest way to deploy the plugin in your cluster is to run this command
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/dsa_plugin?ref=<REF>
daemonset.apps/intel-dsa-plugin created
Where <REF>
needs to be substituted with the desired git ref, e.g. main
.
Nothing else is needed. But if you want to deploy a customized version of the plugin read further.
There's a sample DSA initcontainer included that provisions DSA devices and workqueues (1 engine / 1 group / 1 wq (user/dedicated)), to deploy:
$ kubectl apply -k deployments/dsa_plugin/overlays/dsa_initcontainer/
The provisioning script and template are available for customization.
The provisioning config can be optionally stored in the ProvisioningConfig configMap which is then passed to initcontainer through the volume mount.
There's also a possibility for a node specific congfiguration through passing a nodename via NODE_NAME into initcontainer's environment and passing a node specific profile via configMap volume mount.
To create a custom provisioning config:
$ kubectl create configmap --namespace=inteldeviceplugins-system intel-dsa-config --from-file=demo/dsa.conf
$ export INTEL_DEVICE_PLUGINS_SRC=/path/to/intel-device-plugins-for-kubernetes
$ git clone https://github.com/intel/intel-device-plugins-for-kubernetes ${INTEL_DEVICE_PLUGINS_SRC}
To deploy the dsa plugin as a daemonset, you first need to build a container image for the plugin and ensure that is visible to your nodes.
The following will use docker
to build a local container image called
intel/intel-dsa-plugin
with the tag devel
.
The image build tool can be changed from the default docker
by setting the BUILDER
argument
to the Makefile
.
$ cd ${INTEL_DEVICE_PLUGINS_SRC}
$ make intel-dsa-plugin
...
Successfully tagged intel/intel-dsa-plugin:devel
You can then use the example DaemonSet YAML file provided to deploy the plugin. The default kustomization that deploys the YAML as is:
$ kubectl apply -k deployments/dsa_plugin
daemonset.apps/intel-dsa-plugin created
For development purposes, it is sometimes convenient to deploy the plugin 'by hand' on a node. In this case, you do not need to build the complete container image, and can build just the plugin.
First we build the plugin:
$ cd ${INTEL_DEVICE_PLUGINS_SRC}
$ make dsa_plugin
Now we can run the plugin directly on the node:
$ sudo -E ${INTEL_DEVICE_PLUGINS_SRC}/cmd/dsa_plugin/dsa_plugin
device-plugin registered
You can verify the plugin has been registered with the expected nodes by searching for the relevant resource allocation status on the nodes:
$ kubectl get nodes -o go-template='{{range .items}}{{.metadata.name}}{{"\n"}}{{range $k,$v:=.status.allocatable}}{{" "}}{{$k}}{{": "}}{{$v}}{{"\n"}}{{end}}{{end}}' | grep '^\([^ ]\)\|\( dsa\)'
master
dsa.intel.com/wq-user-dedicated: 2
dsa.intel.com/wq-user-shared: 8
node1
dsa.intel.com/wq-user-dedicated: 4
dsa.intel.com/wq-user-shared: 20
We can test the plugin is working by deploying the provided example accel-config test image.
-
Build a Docker image with an accel-config tests:
$ make dsa-accel-config-demo ... Successfully tagged dsa-accel-config-demo:devel
-
Create a pod running unit tests off the local Docker image:
$ kubectl apply -f ${INTEL_DEVICE_PLUGINS_SRC}/demo/dsa-accel-config-demo-pod.yaml pod/dsa-accel-config-demo created
-
Wait until pod is completed:
$ kubectl get pods |grep dsa-accel-config-demo dsa-accel-config-demo 0/1 Completed 0 31m
-
Review the job's logs:
$ kubectl logs dsa-accel-config-demo | tail [debug] PF in sub-task[6], consider as passed [debug] PF in sub-task[7], consider as passed [debug] PF in sub-task[8], consider as passed [debug] PF in sub-task[9], consider as passed [debug] PF in sub-task[10], consider as passed [debug] PF in sub-task[11], consider as passed [debug] PF in sub-task[12], consider as passed [debug] PF in sub-task[13], consider as passed [debug] PF in sub-task[14], consider as passed [debug] PF in sub-task[15], consider as passed
If the pod did not successfully launch, possibly because it could not obtain the DSA resource, it will be stuck in the
Pending
status:$ kubectl get pods NAME READY STATUS RESTARTS AGE dsa-accel-config-demo 0/1 Pending 0 7s
This can be verified by checking the Events of the pod:
$ kubectl describe pod dsa-accel-config-demo | grep -A3 Events: Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 2m26s default-scheduler 0/1 nodes are available: 1 Insufficient dsa.intel.com/wq-user-dedicated, 1 Insufficient dsa.intel.com/wq-user-shared.