---
description: Learn how to configure Docker Compose to use NVIDIA GPUs with CUDA-based containers
keywords: documentation, docs, docker, compose, GPU access, NVIDIA, samples
title: Run Docker Compose services with GPU access 
linkTitle: Enable GPU support
weight: 90
aliases:
- /compose/gpu-support/
---

Compose services can define GPU device reservations if the Docker host contains such devices and the Docker Daemon is set accordingly. For this, make sure you install the [prerequisites](/manuals/engine/containers/resource_constraints.md#gpu) if you haven't already done so.

The examples in the following sections focus specifically on providing service containers access to GPU devices with Docker Compose. 

## Enabling GPU access to service containers

GPUs are referenced in a `compose.yaml` file using the [device](/reference/compose-file/deploy.md#devices) attribute from the Compose Deploy specification, within your services that need them.

This provides more granular control over a GPU reservation as custom values can be set for the following device properties: 

- `capabilities`. This value is specified as a list of strings. For example, `capabilities: [gpu]`. You must set this field in the Compose file. Otherwise, it returns an error on service deployment.
- `count`. Specified as an integer or the value `all`, represents the number of GPU devices that should be reserved (providing the host holds that number of GPUs). If `count` is set to `all` or not specified, all GPUs available on the host are used by default.
- `device_ids`. This value, specified as a list of strings, represents GPU device IDs from the host. You can find the device ID in the output of `nvidia-smi` on the host. If no `device_ids` are set, all GPUs available on the host are used by default.
- `driver`. Specified as a string, for example `driver: 'nvidia'`
- `options`. Key-value pairs representing driver specific options.


> [!IMPORTANT]
>
> You must set the `capabilities` field. Otherwise, it returns an error on service deployment.

> [!NOTE]
>
> `count` and `device_ids` are mutually exclusive. You must only define one field at a time.

For more information on these properties, see the [Compose Deploy Specification](/reference/compose-file/deploy.md#devices).

### Example of a Compose file for running a service with access to 1 GPU device

```yaml
services:
  test:
    image: nvidia/cuda:12.9.0-base-ubuntu22.04
    command: nvidia-smi
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
```

Run with Docker Compose:

```console
$ docker compose up
Creating network "gpu_default" with the default driver
Creating gpu_test_1 ... done
Attaching to gpu_test_1    
test_1  | +-----------------------------------------------------------------------------+
test_1  | | NVIDIA-SMI 450.80.02    Driver Version: 450.80.02    CUDA Version: 11.1     |
test_1  | |-------------------------------+----------------------+----------------------+
test_1  | | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
test_1  | | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
test_1  | |                               |                      |               MIG M. |
test_1  | |===============================+======================+======================|
test_1  | |   0  Tesla T4            On   | 00000000:00:1E.0 Off |                    0 |
test_1  | | N/A   23C    P8     9W /  70W |      0MiB / 15109MiB |      0%      Default |
test_1  | |                               |                      |                  N/A |
test_1  | +-------------------------------+----------------------+----------------------+
test_1  |                                                                                
test_1  | +-----------------------------------------------------------------------------+
test_1  | | Processes:                                                                  |
test_1  | |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
test_1  | |        ID   ID                                                   Usage      |
test_1  | |=============================================================================|
test_1  | |  No running processes found                                                 |
test_1  | +-----------------------------------------------------------------------------+
gpu_test_1 exited with code 0

```

On machines hosting multiple GPUs, the `device_ids` field can be set to target specific GPU devices and `count` can be used to limit the number of GPU devices assigned to a service container. 

You can use `count` or `device_ids` in each of your service definitions. An error is returned if you try to combine both, specify an invalid device ID, or use a value of count that’s higher than the number of GPUs in your system.

```console
$ nvidia-smi   
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.80.02    Driver Version: 450.80.02    CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla T4            On   | 00000000:00:1B.0 Off |                    0 |
| N/A   72C    P8    12W /  70W |      0MiB / 15109MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  Tesla T4            On   | 00000000:00:1C.0 Off |                    0 |
| N/A   67C    P8    11W /  70W |      0MiB / 15109MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  Tesla T4            On   | 00000000:00:1D.0 Off |                    0 |
| N/A   74C    P8    12W /  70W |      0MiB / 15109MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   3  Tesla T4            On   | 00000000:00:1E.0 Off |                    0 |
| N/A   62C    P8    11W /  70W |      0MiB / 15109MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
```

## Access specific devices

To allow access only to GPU-0 and GPU-3 devices:

```yaml
services:
  test:
    image: tensorflow/tensorflow:latest-gpu
    command: python -c "import tensorflow as tf;tf.test.gpu_device_name()"
    deploy:
      resources:
        reservations:
          devices:
          - driver: nvidia
            device_ids: ['0', '3']
            capabilities: [gpu]

```
