# Intel FPGA device plugin for Kubernetes

# Table of Contents

* [Introduction](#introduction)
* [Component overview](#component-overview)
* [FPGA modes](#fpga-modes)
* [Installation](#installation)
    * [Pre-built images](#pre-built-images)
    * [Dependencies](#dependencies)
    * [Getting the source code](#getting-the-source-code)
    * [Verify node kubelet config](#verify-node-kubelet-config)
    * [Deploying as a DaemonSet](#deploying-as-a-daemonset)
        * [Create a service account](#create-a-service-account)
        * [Deploying `region` mode](#deploying-region-mode)
        * [Deploying `af` mode](#deploying-af-mode)
        * [Deploy the DaemonSet](#deploy-the-daemonset)
        * [Verify plugin registration](#verify-plugin-registration)
        * [Building the plugin image](#building-the-plugin-image)
    * [Deploy by hand](#deploy-by-hand)
        * [Build FPGA device plugin](#build-fpga-device-plugin)
        * [Run FPGA device plugin in af mode](#run-fpga-device-plugin-in-af-mode)
        * [Run FPGA device plugin in region mode](#run-fpga-device-plugin-in-region-mode)
* [Next steps](#next-steps)

# Introduction

This FPGA device plugin is part of a collection of Kubernetes components found within this
repository that enable integration of Intel FPGA hardware into Kubernetes.

The following hardware platforms are supported:

- Intel Arria 10
- Intel Stratix 10

The components support the [Open Programmable Acceleration Engine (OPAE)](https://opae.github.io/latest/index.html)
interface.

The components together implement the following features:

- discovery of pre-programmed accelerator functions
- discovery of programmable regions
- orchestration of FPGA programming
- access control for FPGA hardware

# Component overview

The following components are part of this repository, and work together to support Intel FPGAs under
Kubernetes:

-   [FPGA device plugin](README.md) (this component)

    A Kubernetes [device plugin](https://kubernetes.io/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/)
    that discovers available FPGA resources on a node and advertises them to the Kubernetes control plane
    via the node kubelet.

-   [FPGA admission controller webhook](../fpga_admissionwebhook/README.md)

    A Kubernetes [admission controller webhook](https://kubernetes.io/docs/reference/access-authn-authz/extensible-admission-controllers/)
    which can be used to dynamically convert logical resource names in pod specifications into actual FPGA
    resource names, as advertised by the device plugin.

    The webhook can also set environment variables to instruct the CRI-O prestart hook to program the FPGA
    before launching the container.

-   [FPGA CRI-O prestart hook](../fpga_crihook/README.md)

    A [CRI-O](https://github.com/cri-o/cri-o) prestart hook that, upon instruction from the FPGA admission
    controller, allocates and programs the FPGA before the container is launched.

The repository also contains an [FPGA helper tool](../fpga_tool/README.md) that may be useful during
development, initial deployment and debugging.

# FPGA modes

The FPGA plugin set can run in one of two modes:

- `region` mode, where the plugins locate and advertise
  regions of the FPGA, and facilitate programing of those regions with the
  requested bistreams.
- `af` mode, where the FPGA bitstreams are already loaded
  onto the FPGA, and the plugins discover and advertises the existing
  Accelerator Functions (AF).

The example YAML deployments described in this document only currently support
`af` mode. To utilise `region` mode, either modify the existing YAML appropriately,
or deploy 'by hand'.

Overview diagrams of `af` and `region` modes are below:

region mode:

![Overview of `region` mode](pictures/FPGA-region.png)

af mode:

![Overview of `af` mode](pictures/FPGA-af.png)

# Installation

The below sections cover how to obtain, build and install this component.

Components can generally be installed either using DaemonSets or running them
'by hand' on each node.

## Pre-built images

Pre-built images of the components are available on the [Docker hub](https://hub.docker.com/u/intel).
These images are automatically built and uploaded to the hub from the latest `master` branch of
this repository.

Release tagged images of the components are also available on the Docker hub, tagged with their
release version numbers (of the form `x.y.z`, matching the branch/tag release number in this repo).

The deployment YAML files supplied with these components in this repository use the images with the
`devel` tag by default. If you do not build your own local images, then your Kubernetes cluster may
pull down the `devel` images from the Docker hub by default.

To use the release tagged versions of the images, edit the YAML deployment files appropriately.

The following images are available on the Docker hub:

- [The FPGA plugin](https://hub.docker.com/r/intel/intel-fpga-plugin)
- [The FPGA admisson webhook](https://hub.docker.com/r/intel/intel-fpga-admissionwebhook)
- [The FPGA CRI-O prestart hook (in the `initcontainer` image)](https://hub.docker.com/r/intel/intel-fpga-initcontainer)

## Dependencies

All components have the same basic dependencies as the
[generic plugin framework dependencies](../../README.md#about)

To obtain a fully operational FPGA enabled cluster, you must install all three
major components:

-   [FPGA device plugin](README.md) (this component)
-   [FPGA admission controller webhook](../fpga_admissionwebhook/README.md)
-   [FPGA prestart CRI-O hook](../fpga_crihook/README.md)

The CRI-O hook is only *required* if `region` mode is being used, but is installed by default by the
[FPGA plugin DaemonSet YAML](../../deployments/fpga_plugin/fpga_plugin.yaml), and is benign
in `af` mode.

If using the `af` mode, and therefore *not* using the
CRI-O prestart hook, runtimes other than CRI-O can be used (that is, the CRI-O hook presently
*only* works with the CRI-O runtime).

The FPGA device plugin requires a Linux Kernel FPGA driver to be installed and enabled to
operate. The plugin supports the use of either of following two drivers, and auto detects
which is present and thus to use:

- The Linux Kernel in-tree [DFL](https://www.kernel.org/doc/html/latest/fpga/dfl.html) driver
- The out of tree [OPAE](https://opae.github.io/latest/docs/drv_arch/drv_arch.html) driver

Install this component (FPGA device plugin) first, and then follow the links
and instructions to install the other components.

## Getting the source code

To obtain the YAML files used for deployment, or to obtain the source tree if you intend to
do a hand-deployment or build your own image, you will require access to the source code:

```bash
$ mkdir -p $(go env GOPATH)/src/github.com/intel
$ git clone https://github.com/intel/intel-device-plugins-for-kubernetes $(go env GOPATH)/src/github.com/intel/intel-device-plugins-for-kubernetes
```

## Verify node kubelet config

Every node that will be running the FPGA plugin must have the
[kubelet device-plugins](https://kubernetes.io/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/)
configured. For each node, check that the kubelet device plugin socket exists:

```bash
$ ls /var/lib/kubelet/device-plugins/kubelet.sock
/var/lib/kubelet/device-plugins/kubelet.sock
```

## Deploying as a DaemonSet

You can deploy the plugin in either of the modes, using the
[DaemonSet YAML](../../deployments/fpga_plugin/fpga_plugin.yaml)
supplied. Details are in the following sections. Actions common to both deployment modes are detailed
first. Mode specific actions are then detailed.

If you intend to deploy your own image, you will need to reference the
[image build section](#build-the-plugin-image) first.

If you do not want to deploy the `devel` tagged image, you will need to edit the
YAML deployment files to reference your required image.

### For beta testing: new deployment model

The FPGA plugin deployment is currently being rewritten to enable
straight-forward deployment of both `af` and
`region` modes. The deployment has two steps:

1. Run `scripts/fpga-plugin-prepare-for-kustomization.sh`. This will
   create the necessary secrets: a key and a signed certificate for
   the FPGA admission controller.

2. Depending on the FPGA mode, run either
   ```bash
   $ kubectl create -k deployments/fpga_plugin/overlays/af
   ```
   or
   ```bash
   $ kubectl create -k deployments/fpga_plugin/overlays/region
   ```
   This will create the service account and deploy
   both the FPGA plugin and the admission controller in the chosen mode.

This deployment model is under development. The remaining part of this
document goes through the current deployment model: here for the
FPGA plugin and in the next document for the FPGA admission controller.

### Create a service account

To deploy the plugin in a production cluster, create a service account
for the plugin:

```bash
$ kubectl create -f deployments/fpga_plugin/fpga_plugin_service_account.yaml
serviceaccount/intel-fpga-plugin-controller created
clusterrole.rbac.authorization.k8s.io/node-getter created
clusterrolebinding.rbac.authorization.k8s.io/get-nodes created
```

### Deploying `region` mode

To deploy the FPGA plugin DaemonSet in `region` mode, you need to set the plugin
mode annotation on all of your nodes, otherwise the FPGA plugin will run in its default
`af` mode.

```bash
$ kubectl annotate node --all 'fpga.intel.com/device-plugin-mode=region'
```

### Deploying `af` mode

To deploy the FPGA plugin DaemonSet in `af` mode, you do not need to set the mode annotation on
your nodes, as the FPGA plugin runs in `af` mode by default.

> **Note:** The FPGA plugin [DaemonSet YAML](../../deployments/fpga_plugin/fpga_plugin.yaml)
> also deploys the [FPGA CRI-O hook](../fpga_criohook) `initcontainer` image, but it will be
> benign (un-used) when running the FPGA plugin in `af` mode.

### Deploy the DaemonSet

You can then use the example DaemonSet YAML file provided to deploy the plugin.

```bash
$ kubectl create -f deployments/fpga_plugin/fpga_plugin.yaml
daemonset.apps/intel-fpga-plugin created
```

### Verify plugin registration

Verify the FPGA plugin has been deployed on the nodes. The below shows the output
you can expect in `region` mode, but similar output should be expected for `af`
mode:

```bash
$ kubectl describe nodes | grep fpga.intel.com
fpga.intel.com/region-ce48969398f05f33946d560708be108a:  1
fpga.intel.com/region-ce48969398f05f33946d560708be108a:  1
```

### Building the plugin image

If you need to build your own image from sources, and are not using the images
available on the Docker Hub, follow the below details.

> **Note:** The FPGA plugin [DaemonSet YAML](../../deployments/fpga_plugin/fpga_plugin.yaml)
> also deploys the [FPGA CRI-O hook](../fpga_criohook) `initcontainer` image as well. You may
> also wish to build that image locally before deploying the FPGA plugin to avoid deploying
> the Docker hub default image.

The following will use `docker` to build a local container image called
`intel/intel-fpga-plugin` with the tag `devel`.
The image build tool can be changed from the default docker by setting the `BUILDER` argument
to the [Makefile](../../Makefile).

```bash
$ make intel-fpga-plugin
...
Successfully tagged intel/intel-fpga-plugin:devel
```

This image launches `fpga_plugin` in `af` mode by default.

To use your own container image, modify the
[`deployments/fpga_plugin/fpga_plugin.yaml`](../../deployments/fpga_plugin/fpga_plugin.yaml)
file.

## Deploy by hand

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.

> **Note:** The FPGA plugin has a number of other associated items that may also need
> to be configured or installed. It is recommended you reference the actions of the
> DaemonSet YAML deployment for more details.

### Build FPGA device plugin

When deploying by hand, you only need to build the plugin itself, and not the whole
container image:

```bash
$ cd $(go env GOPATH)/src/github.com/intel/intel-device-plugins-for-kubernetes
$ make fpga_plugin
```

### Run FPGA device plugin in af mode

```bash
$ export KUBE_CONF=/var/run/kubernetes/admin.kubeconfig # path to kubeconfig with admin's credentials
$ export NODE_NAME="<node name>" # if the node's name was overridden and differs from hostname
$ sudo -E $(go env GOPATH)/src/github.com/intel/intel-device-plugins-for-kubernetes/cmd/fpga_plugin/fpga_plugin -mode af -kubeconfig $KUBE_CONF
FPGA device plugin started in af mode
device-plugin start server at: /var/lib/kubelet/device-plugins/fpga.intel.com-af-f7df405cbd7acf7222f144b0b93acd18.sock
device-plugin registered
```

> **Note**: It is also possible to run the FPGA device plugin using a non-root user. To do this,
the nodes' DAC rules must be configured to device plugin socket creation and kubelet registration.
Furthermore, the deployments `securityContext` must be configured with appropriate `runAsUser/runAsGroup`.

### Run FPGA device plugin in region mode

```bash
$ export KUBE_CONF=/var/run/kubernetes/admin.kubeconfig # path to kubeconfig with admin's credentials
$ export NODE_NAME="<node name>" # if the node's name was overridden and differs from hostname
$ sudo -E $(go env GOPATH)/src/github.com/intel/intel-device-plugins-for-kubernetes/cmd/fpga_plugin/fpga_plugin -mode region -kubeconfig $KUBE_CONF
FPGA device plugin started in region mode
device-plugin start server at: /var/lib/kubelet/device-plugins/fpga.intel.com-region-ce48969398f05f33946d560708be108a.sock
device-plugin registered
```
# Next steps

Continue installation with the [FPGA admission controller webhook](../fpga_admissionwebhook/README.md).