# Use GPUs with Amazon ECS Managed Instances
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Amazon ECS Managed Instances supports GPU-accelerated computing for workloads such as machine learning, high-performance computing, and video processing through the following Amazon EC2 instance types. For more information about instance types supported by Amazon ECS Managed Instances, see [Amazon ECS Managed Instances instance types](managed-instances-instance-types.md).

The following is a subset of GPU-based instance types supported on Amazon ECS Managed Instances:
+ `g4dn`: Powered by NVIDIA T4 GPUs, suitable for machine learning inference, computer vision, and graphics-intensive applications.
+ `g5`: Powered by NVIDIA A10G GPUs, offering higher performance for graphics-intensive applications and machine learning workloads.
+ `p3`: Powered by NVIDIA V100 GPUs, designed for high-performance computing and deep learning training.
+ `p4d`: Powered by NVIDIA A100 GPUs, offering the highest performance for for machine learning training and high-performance computing.

When you use GPU-enabled instance types with Amazon ECS Managed Instances, the NVIDIA drivers and CUDA toolkit are pre-installed on the instance, making it easier to run GPU-accelerated workloads.

## GPU-enabled instance selection
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To select GPU-enabled instance types for your Amazon ECS Managed Instances workloads, use the `instanceRequirements` object in the launch template of the capacity provider. The following snippet shows the attributes that can be used for selecting GPU-enabled instances.

```
{
  "instanceRequirements": {
    "acceleratorTypes": "gpu",
    "acceleratorCount": 1,
    "acceleratorManufacturers": ["nvidia"]
  }
}
```

The following snippet shows the attributes that can be used to specify GPU-enabled instance types in the launch template.

```
{
  "instanceRequirements": {
    "allowedInstanceTypes": ["g4dn.xlarge", "p4de.24xlarge"]
  }
}
```

## GPU-enabled container images
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To use GPUs in your containers, you need to use container images that contain the necessary GPU libraries and tools. NVIDIA provides several pre-built container images that you can use as a base for your GPU workloads, including the following:
+ `nvidia:cuda`: Base images with the CUDA toolkit for GPU computing.
+ `tensorflow/tensorflow:latest-gpu`: TensorFlow with GPU support.
+ `pytorch/pytorch:latest-cuda`: PyTorch with GPU support.

For an example task definition for Amazon ECS on Amazon ECS Managed Instances that involves the use of GPUs, see [Specifying GPUs in an Amazon ECS task definition](ecs-gpu-specifying.md).