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@ -82,7 +82,7 @@ Hardware acceleration users for Raspberry Pi V4L2 will need to mount their `/dev
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### Hardware Acceleration
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Many desktop application will need access to a GPU to function properly and even some Desktop Environments have compisitor effects that will not function without a GPU. This is not a hard requirement and all base images will function without a video device mounted into the container.
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Many desktop applications need access to a GPU to function properly and even some Desktop Environments have compositor effects that will not function without a GPU. However this is not a hard requirement and all base images will function without a video device mounted into the container.
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#### Intel/ATI/AMD
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@ -97,9 +97,9 @@ We will automatically ensure the abc user inside of the container has the proper
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#### Nvidia
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Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:
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https://github.com/NVIDIA/nvidia-docker
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https://github.com/NVIDIA/nvidia-container-toolkit
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We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the container.
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We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-container-toolkit is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the container.
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#### Arm Devices
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