This document describes setting up transcoding in Memories, specifically using hardware acceleration. Hardware acceleration can significantly improve transcoding performance, especially for high resolution videos. Memories supports transcoding using **CPU**, **VA-API** and **NVENC**.
## Overview
Newer Intel processors come with a feature called QuickSync that can significantly boost transcoding performance (4-5x improvement over x264 is common). QuickSync can be used for hardware accelerated transcoding using the VA-API in ffmpeg.
Note: VA-API acceleration may also work with some AMD GPUs.
To configure VAAPI, you need to have `/dev/dri` available to the Nextcloud instance with the `www-data` in the group owning the drivers. You also need the correct drivers and a compatible version of ffmpeg installed.
NVIDIA GPUs support hardware transcoding using NVENC.
!!! tip "Hardware acceleration is optional"
Hardware acceleration is optional and not required for Memories to function. If you do not have hardware acceleration, Memories will use the CPU for transcoding.
!!! bug "Filing bugs related to transcoding"
If you have issues with hardware transcoding, reach out for [help](/faq/#getting-help). Make sure you include details about your setup such as how the transcoder is set up, the version of each component and **the logs from the transcoder**.
[go-vod](https://github.com/pulsejet/go-vod), the transcoder of Memories, ships with a Dockerfile that already includes the latest ffmpeg and VA-API drivers. To set up an external transcoder, follow these steps.
1. Clone the go-vod repository. Make sure you use the correct tag, which can be found in the admin panel. Note that this is **not** the same as the version of Memories you run.
Make sure you always use the correct version of go-vod corresponding to your Memories installation. If you use a different version, the admin panel will show a warning and transcoding may not work properly.
1. Use a `docker-compose` file that builds the go-vod container and mounts the Nextcloud data directories to it. The directory containing the `docker-compose.yml` must contain the `go-vod` repository in it. You can then run `docker compose build` to build the image and `docker compose up -d` to start the containers.
In this example, the VA-API device `/dev/dri/renderD128` is passed to the container, along with the Nextcloud data directory (as readonly). All volumnes must be mounted at the same location as the Nextcloud container.
1. You can now configure the go-vod connect address in the Memories admin panel to point to the external container. go-vod uses port `47788` by default, so in our example the **connection address** would be set to **`go-vod:47788`**.
With Nextcloud AIO, you will need to put the container into the `nextcloud-aio` network. Also the datadir of AIO needs to be mounted at the same place like in its Netxcloud container into the go-vod container. Usually this would be `nextcloud_aio_nextcloud_data:/mnt/ncdata:ro` or `$NEXTCLOUD_DATADIR:/mnt/ncdata:ro`.
See the instructions [here](https://github.com/nextcloud/all-in-one#how-to-enable-hardware-transcoding-for-nextcloud).
You can run a similar setup without `docker-compose` by building the go-vod container manually. Make sure that the Nextcloud and go-vod containers are in the same network and that the Nextcloud data directories are mounted at the same locations in both containers.
Memories ships with an internal transcoder binary that you can directly use. In this case, you must install the drivers and ffmpeg on the same host as Nextcloud, and Memories will automatically handling starting and communicating with go-vod. This is also the default setup when you enable transcoding without hardware acceleration.
!!! danger "Advanced usage only"
In most cases, it is easier to use an external transcoder when you need hardware acceleration.
The internal transcoder is only suitable for CPU transcoding or if you do not use Docker.
!!! tip "NVENC"
These instructions mostly focus on VA-API. For NVENC, you may find further useful
pointers in [this](https://github.com/pulsejet/go-vod/blob/master/build-ffmpeg-nvidia.sh) build script.
### Bare Metal
If you are running Nextcloud on bare metal, you can install the drivers and ffmpeg directly on the host. You need to make sure that the `www-data` user has access to the drivers. You can do this by adding the `www-data` user to the appropriate groups.
In some cases, you may need to build the drivers and `ffmpeg` from source. For example, the available version of the media driver for the current debian image used by Nextcloud only supports upto Ice Lake CPUs. [This script](https://github.com/pulsejet/go-vod/blob/master/build-ffmpeg.sh) for VA-API or [this one](https://github.com/pulsejet/go-vod/blob/master/build-ffmpeg-nvidia.sh) for NVENC might be useful.
If you need hardware transcoding and use Docker, it can be significantly easier to use an external transcoder. See [above](#external-transcoder) for instructions.
The `linuxserver/nextcloud` image is based on Alpine. You can add the following to the `docker-compose.yml` file to install the VA-API drivers and use the internal transcoder directly.
When using the internal transcoder, the logs go to `/tmp/go-vod/<instance-id>.log`, where `<instance-id` is a unique ID for your Nextcloud instance that can be found in `config.php`. You can view them as illustrated below.