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NVIDIA Hardware Acceleration on Linux

Difficulty Setup Time

A number of plugins for Unmanic support hardware acceleration that utilise an NVIDIA GPU. This includes hardware acceleration (HWA) of video decoding/encoding in tools like FFmpeg or HandBrake CLI using the NVIDIA NVDEC/NVENC decoder/encoder.

Follow these instructions to configure the Unmanic Docker container for running FileBot as a Post-processor function.

Instructions:​

1) Check GPU Support​

You can find an official list of NVIDIA Graphics Cards and their supported codecs Here.

Check that your GPU is listed and is capable of doing what you want it to.

2) Install GPU Driver​

Ensure you have installed the NVIDIA drivers.

This is required even if you intend to run Unmanic within a Docker container.

You can download the latest NVIDIA GPU driver from here.

note

The minimum required NVIDIA driver version is 418.30 for this to work in Linux.

tip

It is recommended to also patch drivers the drivers by following the instructions here. This project will remove the restriction on maximum number of simultaneous NVENC video encoding sessions imposed by Nvidia to consumer-grade GPUs.

3) FFmpeg installation with NVENC support​

note

Only worry about this if you are running Unmanic natively on Linux. The Docker image has FFmpeg pre-installed with support for NVENC/NVDEC

Install FFmpeg for your operating system.

It is recommend to use the Jellyfin FFmpeg builds, however any recent release of FFmpeg will work fine.

To ensure your FFmpeg installation is capable of running the NVENC encoders, run this command:

for i in encoders decoders filters; do echo $i:; ffmpeg -hide_banner -${i} | egrep -i "npp|cuvid|nvenc|cuda|nvdec"; done

You should see a list of available encoders and decoders.

4) Running in Docker with NVENC support​

Installing the NVIDIA Container Toolkit​

If you intend to use Unmanic inside a Docker container, you will also need to pass through the required devices to the container. With NVIDIA this is done by installing the nvidia-docker2 package on your host.

Once you have followed these steps, you can test that the Unmanic Docker container can use the NVENC hardware by running:

docker run --rm --gpus all --entrypoint="" josh5/unmanic nvidia-smi

You should see the following output:

Sun Apr 17 05:31:44 2022       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.54       Driver Version: 510.54       CUDA Version: 11.6     |
|-------------------------------+----------------------+----------------------+
| 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  NVIDIA GeForce ...  Off  | 00000000:01:00.0  On |                  N/A |
|  0%   34C    P8    N/A / 120W |    185MiB /  4096MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

Creating the Docker container​

  PUID=$(id -u)
  PGID=$(id -g)

  # CONFIG_DIR - Where you settings are saved
  CONFIG_DIR=/config

  # LIBRARY_DIR - The location/locations of your library
  LIBRARY_DIR=/library

  # CACHE_DIR - A tmpfs or and folder for temporary conversion files
  CACHE_DIR=/tmp/unmanic
  
  # NVIDIA_VISIBLE_DEVICES - The GPUs that will be accessible to the container
  NVIDIA_VISIBLE_DEVICES=all

  docker run -ti --rm \
      -e PUID=${PUID} \
      -e PGID=${PGID} \
      -e NVIDIA_VISIBLE_DEVICES=${NVIDIA_VISIBLE_DEVICES} \
      --runtime=nvidia \
      -p 8888:8888 \
      -v ${CONFIG_DIR}:/config \
      -v ${LIBRARY_DIR}:/library \
      -v ${CACHE_DIR}:/tmp/unmanic \
      josh5/unmanic:latest