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open-nomad/website/content/plugins/devices/nvidia.mdx
Seth Hoenig 684abb9e28 docs: update nvidia driver documentation 
notably:
- name of the compiled binary is 'nomad-device-nvidia', not 'nvidia-gpu'
- link to Nvidia docs for installing the container runtime toolkit
- list docker v19.03 as minimum version, to track with nvidia's new container runtime toolkit
2022-05-02 09:11:05 -05:00

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---
layout: docs
page_title: 'Device Plugins: Nvidia'
description: The Nvidia Device Plugin detects and makes Nvidia devices available to tasks.
---
# Nvidia GPU Device Plugin
Name: `nomad-device-nvidia`
The Nvidia device plugin is used to expose Nvidia GPUs to Nomad.
~> **Note**: The Nvidia device plugin setup has changed in Nomad 1.2. You must
add a [`plugin`] block to your clients configuration and install the
[external Nvidia device plugin][nvidia_plugin_download] into their
[`plugin_dir`] prior to upgrading. See plugin options below for an example.
Note the job specification remains the same.
## Fingerprinted Attributes
<table>
<thead>
<tr>
<th>Attribute</th>
<th>Unit</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<tt>memory</tt>
</td>
<td>MiB</td>
</tr>
<tr>
<td>
<tt>power</tt>
</td>
<td>W (Watt)</td>
</tr>
<tr>
<td>
<tt>bar1</tt>
</td>
<td>MiB</td>
</tr>
<tr>
<td>
<tt>driver_version</tt>
</td>
<td>string</td>
</tr>
<tr>
<td>
<tt>cores_clock</tt>
</td>
<td>MHz</td>
</tr>
<tr>
<td>
<tt>memory_clock</tt>
</td>
<td>MHz</td>
</tr>
<tr>
<td>
<tt>pci_bandwidth</tt>
</td>
<td>MB/s</td>
</tr>
<tr>
<td>
<tt>display_state</tt>
</td>
<td>string</td>
</tr>
<tr>
<td>
<tt>persistence_mode</tt>
</td>
<td>string</td>
</tr>
</tbody>
</table>
## Runtime Environment
The `nvidia-gpu` device plugin exposes the following environment variables:
- `NVIDIA_VISIBLE_DEVICES` - List of Nvidia GPU IDs available to the task.
### Additional Task Configurations
Additional environment variables can be set by the task to influence the runtime
environment. See [Nvidia's
documentation](https://github.com/NVIDIA/nvidia-container-runtime#environment-variables-oci-spec).
## Installation Requirements
In order to use the `nomad-device-nvidia` device driver the following prerequisites must be met:
1. GNU/Linux x86_64 with kernel version > 3.10
2. NVIDIA GPU with Architecture > Fermi (2.1)
3. NVIDIA drivers >= 340.29 with binary `nvidia-smi`
4. Docker v19.03+
### Container Toolkit Installation
Follow the [NVIDIA Container Toolkit installation instructions][nvidia_container_toolkit]
from Nvidia to prepare a machine to use docker containers with Nvidia GPUs. You should
be able to run this simple command to test your environment and produce meaningful
output.
```shell
docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
```
## Plugin Configuration
```hcl
plugin "nomad-device-nvidia" {
config {
enabled = true
ignored_gpu_ids = ["GPU-fef8089b", "GPU-ac81e44d"]
fingerprint_period = "1m"
}
}
```
The `nomad-device-nvidia` device plugin supports the following configuration in the agent
config:
- `enabled` `(bool: true)` - Control whether the plugin should be enabled and running.
- `ignored_gpu_ids` `(array<string>: [])` - Specifies the set of GPU UUIDs that
should be ignored when fingerprinting.
- `fingerprint_period` `(string: "1m")` - The period in which to fingerprint for
device changes.
## Limitations
The Nvidia integration only works with drivers who natively integrate with
Nvidia's [container runtime
library](https://github.com/NVIDIA/libnvidia-container).
Nomad has tested support with the [`docker` driver][docker-driver]. Support for
[`lxc`][lxc-driver] should be possible by installing the [Nvidia hook][nvidia_hook]
but is not tested or documented by Nomad.
## Source Code & Compiled Binaries
The source code for this plugin can be found at hashicorp/nomad-device-nvidia. You
can also find pre-built binaries on the [releases page][nvidia_plugin_download].
## Examples
Inspect a node with a GPU:
```shell-session
$ nomad node status 4d46e59f
// ...TRUNCATED...
Device Resource Utilization
nvidia/gpu/Tesla K80[GPU-e1f6f4f1-1ea5-7b9d-5f03-338a9dc32416] 0 / 11441 MiB
```
Display detailed statistics on a node with a GPU:
```shell-session
$ nomad node status -stats 4d46e59f
// ...TRUNCATED...
Device Resource Utilization
nvidia/gpu/Tesla K80[GPU-e1f6f4f1-1ea5-7b9d-5f03-338a9dc32416] 0 / 11441 MiB
// ...TRUNCATED...
Device Stats
Device = nvidia/gpu/Tesla K80[GPU-e1f6f4f1-1ea5-7b9d-5f03-338a9dc32416]
BAR1 buffer state = 2 / 16384 MiB
Decoder utilization = 0 %
ECC L1 errors = 0
ECC L2 errors = 0
ECC memory errors = 0
Encoder utilization = 0 %
GPU utilization = 0 %
Memory state = 0 / 11441 MiB
Memory utilization = 0 %
Power usage = 37 / 149 W
Temperature = 34 C
```
Run the following example job to see that that the GPU was mounted in the
container:
```hcl
job "gpu-test" {
datacenters = ["dc1"]
type = "batch"
group "smi" {
task "smi" {
driver = "docker"
config {
image = "nvidia/cuda:11.0-base"
command = "nvidia-smi"
}
resources {
device "nvidia/gpu" {
count = 1
# Add an affinity for a particular model
affinity {
attribute = "${device.model}"
value = "Tesla K80"
weight = 50
}
}
}
}
}
}
```
```shell-session
$ nomad run example.nomad
==> Monitoring evaluation "21bd7584"
Evaluation triggered by job "gpu-test"
Allocation "d250baed" created: node "4d46e59f", group "smi"
Evaluation status changed: "pending" -> "complete"
==> Evaluation "21bd7584" finished with status "complete"
$ nomad alloc status d250baed
// ...TRUNCATED...
Task "smi" is "dead"
Task Resources
CPU Memory Disk Addresses
0/100 MHz 0 B/300 MiB 300 MiB
Device Stats
nvidia/gpu/Tesla K80[GPU-e1f6f4f1-1ea5-7b9d-5f03-338a9dc32416] 0 / 11441 MiB
Task Events:
Started At = 2019-01-23T18:25:32Z
Finished At = 2019-01-23T18:25:34Z
Total Restarts = 0
Last Restart = N/A
Recent Events:
Time Type Description
2019-01-23T18:25:34Z Terminated Exit Code: 0
2019-01-23T18:25:32Z Started Task started by client
2019-01-23T18:25:29Z Task Setup Building Task Directory
2019-01-23T18:25:29Z Received Task received by client
$ nomad alloc logs d250baed
Wed Jan 23 18:25:32 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.48 Driver Version: 410.48 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla K80 On | 00004477:00:00.0 Off | 0 |
| N/A 33C P8 37W / 149W | 0MiB / 11441MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
```
[docker-driver]: /docs/drivers/docker 'Nomad docker Driver'
[exec-driver]: /docs/drivers/exec 'Nomad exec Driver'
[java-driver]: /docs/drivers/java 'Nomad java Driver'
[lxc-driver]: /plugins/drivers/community/lxc 'Nomad lxc Driver'
[`plugin`]: /docs/configuration/plugin
[`plugin_dir`]: /docs/configuration#plugin_dir
[nvidia_hook]: https://github.com/lxc/lxc/blob/master/hooks/nvidia
[nvidia_plugin_download]: https://releases.hashicorp.com/nomad-device-nvidia/
[nvidia_container_toolkit]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html
[source]: https://github.com/hashicorp/nomad-device-nvidia
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