kops/hooks/nvidia-device-plugin/README.md

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# NVIDIA GPU Driver and DevicePlugin Installation
## Summary
This kops hook container may be used to enable nodes with GPUs to work with
Kubernetes. It is targeted specifically for AWS GPU [instance
types](https://aws.amazon.com/ec2/instance-types/).
It installs the following from web sources.
1. [Nvidia Device Drivers](http://www.nvidia.com/Download/index.aspx)
2. [Cuda Libraries v9.1](https://developer.nvidia.com/cuda-downloads)
3. [nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
4. [docker-ce](https://www.docker.com/community-edition)
Using this hook indicates that you agree to the Nvidia
[licenses](http://www.nvidia.com/content/DriverDownload-March2009/licence.php?lang=us).
## How it works
* This kops hook container runs on a kubernetes node upon every boot.
* It installs onto the host system a systemd oneshot service unit
`nvidia-device-plugin.service` along with setup scripts.
* The systemd unit `nvidia-device-plugin.service` runs and executes the setup
scripts in the host directory `/nvidia-device-plugin`.
* The scripts install the Nvidia device drivers, Cuda libs, Nvidia docker along
with the matching version of docker-ce.
* The scheduling of work in a separate systemd unit outside of this kops hook
is required because it is not possible to upgrade docker-ce on the host from
within a docker container.
## Prerequisites
Although this hook *may* work among many combinatorial versions of software and
images, it has only been tested with the following:
* kops: **1.9**
* kubernetes: 1.10, **1.11**
* OS Image: **`kope.io/k8s-1.10-debian-stretch-amd64-hvm-ebs-2018-05-27`**
* This is most certainly not the default image for kops. The OS image must
be explicitly overridden in the cluster or instancegroup spec.
* Debian stretch is needed because `nvidia-docker` requires a newer version
of `docker-ce >= 18.0`, which is not available in the Debian jessie package
repository. In addition, the Debian jessie kernel was compiled with gcc-7,
while the system packages install gcc-4, thus making the nvidia driver
compilation fail.
* cloud: **AWS**
* This hook will only work on AWS at this moment.
* This is due to the fact that it uses an AWS discovery mechanism to
determine node instancetype, and subsequently install the correct drivers and
configure the optimal settings for the GPU chipsets.
### Test Matrix
This kops hook was developed against the following version combinations.
| Kops Version | Kubernetes Version | GPU Mode | OS Image |
| ------------- | ------------------ | ------------ | -------- |
| 1.10-beta.1 | 1.10 | deviceplugin | kope.io/k8s-1.10-debian-stretch-amd64-hvm-ebs-2018-05-27
| 1.9.1 | 1.11 | deviceplugin | kope.io/k8s-1.10-debian-stretch-amd64-hvm-ebs-2018-05-27
| 1.9.1 | 1.10 | legacy | kope.io/k8s-1.10-debian-stretch-amd64-hvm-ebs-2018-05-27
## Using this DevicePlugin
### Create a Cluster with GPU Nodes
```bash
kops create cluster gpu.example.com \
--zones us-east-1c \
--node-size p2.xlarge \
--node-count 1 \
--image kope.io/k8s-1.10-debian-stretch-amd64-hvm-ebs-2018-05-27 \
--kubernetes-version 1.11.0
```
### Enable the Kops Installation Hook and DevicePlugins
This should be safe to do for all machines, because the hook auto-detects if
the machine is an AWS GPU instancetype and will NO-OP otherwise. Choose
between the DevicePlugin GPU Mode or Legacy Accelerators GPU Mode.
#### (Preferred) DevicePlugin GPU Mode
This mode is:
* Required for kubernetes >= 1.11.0
* Optional for 1.8.0 =< kubernetes <= 1.11.0
For Kubernetes >= 1.11.0 or clusters supporting DevicePlugins
```yaml
# > kops edit instancegroup nodes
spec:
image: kope.io/k8s-1.10-debian-stretch-amd64-hvm-ebs-2018-05-27
hooks:
- execContainer:
image: dcwangmit01/nvidia-device-plugin:0.1.0
### The settings below are only necessary for kubernetes <= 1.11.0, where
### deviceplugins are not enabled by default.
# kubelet:
# featureGates:
# # Enable DevicePlugins
# DevicePlugins: "true"
# # Disable Accelerators (may interfere with DevicePlugins)
# Accelerators: "false"
```
#### (Deprecated) Legacy Accelerators GPU Mode
The legacy `accelerator`
GPU mode is equivalent to the original [GPU hook](/docs/gpu.md).
Accelerators are deprecated in `Kubernetes >= 1.11.0`.
```yaml
# > kops edit instancegroup nodes
spec:
image: kope.io/k8s-1.10-debian-stretch-amd64-hvm-ebs-2018-05-27
hooks:
- execContainer:
image: dcwangmit01/nvidia-device-plugin:0.1.0
environment:
NVIDIA_DEVICE_PLUGIN_MODE: legacy
kubelet:
featureGates:
# Disable DevicePlugins (may interfere with DevicePlugins)
DevicePlugins: "false"
# Enable Accelerators
Accelerators: "true"
```
### Update the cluster
```bash
kops update cluster gpu.example.com --yes
kops rolling-update cluster gpu.example.com --yes
```
### Deploy the Daemonset for the Nvidia DevicePlugin
Only for DevicePlugin GPU Mode, load the deviceplugin daemonset for your
specific environment. This is not required for the Legacy Accelerators GPU
Mode.
```bash
# For kubernetes 1.10
kubectl create -f https://raw.githubusercontent.com/NVIDIA/k8s-device-plugin/v1.10/nvidia-device-plugin.yml
# For kubernetes 1.11
kubectl create -f https://raw.githubusercontent.com/NVIDIA/k8s-device-plugin/v1.11/nvidia-device-plugin.yml
# (Optional) Set permissive toleration to allow daemonset to run anywhere.
# By default this is permissive in case you have tainted your GPU nodes.
kubectl patch daemonset nvidia-device-plugin-daemonset --namespace kube-system \
-p '{ "spec": { "template": { "spec": { "tolerations": [ { "operator": "Exists" } ] } } } }'
```
### Validate that GPUs are Working
#### Deploy a Test Pod
```bash
cat << EOF | kubectl create -f -
apiVersion: v1
kind: Pod
metadata:
name: tf-gpu
spec:
containers:
- name: gpu
image: tensorflow/tensorflow:1.9.0-gpu
imagePullPolicy: IfNotPresent
resources:
limits:
memory: 1024Mi
# ^ Set memory in case default limits are set low
nvidia.com/gpu: 1 # requesting 1 GPUs
# ^ For Legacy Accelerators mode this key must be renamed
# 'alpha.kubernetes.io/nvidia-gpu'
tolerations:
# This toleration will allow the gpu hook to run anywhere
# By default this is permissive in case you have tainted your GPU nodes.
- operator: "Exists"
# ^ If you have a specific taint to target, comment out the above and modify
# the example below
### Example tolerations
# - key: "dedicated"
# operator: "Equal"
# value: "gpu"
# effect: "NoExecute"
EOF
```
#### Validate that GPUs are working
```bash
# Check that nodes are detected to have GPUs
kubectl describe nodes|grep -E 'gpu:\s.*[1-9]'
# Check the logs of the Tensorflow Container to ensure that it ran
kubectl logs tf-gpu
# Show GPU info from within the pod
# Only works in DevicePlugin mode
kubectl exec -it tf-gpu nvidia-smi
# Show Tensorflow detects GPUs from within the pod.
# Only works in DevicePlugin mode
kubectl exec -it tf-gpu -- \
python -c 'from tensorflow.python.client import device_lib; print(device_lib.list_local_devices())'
```