mirror of https://github.com/immich-app/immich.git synced 2025-06-14 03:26:35 +02:00

feat(server): transcoding hardware acceleration (#3171 )

* added transcode configs for nvenc,qsv and vaapi

* updated dev docker compose

* added software fallback

* working vaapi

* minor fixes and added tests

* updated api

* compile libvips

* move hwaccel settings to `hwaccel.yml`

* changed default dockerfile, moved `readdir` call

* removed unused import

* minor cleanup

* fix for arm build

* added documentation, minor fixes

* added intel driver

* updated docs

styling

* uppercase codec and api names

* formatting

* added tests

* updated docs

* removed semicolons

* added link to `hwaccel.yml`

* added newlines

* added `hwaccel` section to docker-compose.prod.yml

* ensure mesa drivers are installed

* switch to mimalloc for sharp

* moved build version and sha256 to json

* let libmfx set the render device

* possible fix for vp9 on qsv

* updated tests

* formatting

* review suggestions

* semicolon

* moved `LD_PRELOAD` to start script

* switched to jellyfin's ffmpeg package

* fixed dockerfile

* use cqp instead of icq for qsv vp9

* updated dockerfile

* added sha256sum for other platforms

* fixtures

2023-08-01 20:56:10 -05:00

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Hardware Transcoding [Experimental]

This feature allows you to use a GPU or Intel Quick Sync to accelerate transcoding and reduce CPU load. Note that hardware transcoding is much less efficient for file sizes. As this is a new feature, it is still experimental and may not work on all systems.

Supported APIs

NVENC
- NVIDIA GPUs
Quick Sync
- Intel CPUs
VAAPI
- GPUs

Limitations

The instructions and configurations here are specific to Docker Compose. Other container engines may require different configuration.
Only Linux and Windows (through WSL2) servers are supported.
WSL2 does not support Quick Sync.
Raspberry Pi is currently not supported.
Two-pass mode is only supported for NVENC. Other APIs will ignore this setting.
Only encoding is currently hardware accelerated, so the CPU is still used for software decoding.
- This is mainly because the original video may not be hardware-decodable.
Hardware dependent
- Codec support varies, but H.264 and HEVC are usually supported.
  - Notably, NVIDIA and AMD GPUs do not support VP9 encoding.
- Newer devices tend to have higher transcoding quality.

Prerequisites

NVENC

You must have the official NVIDIA driver installed on the server.
On Linux (except for WSL2), you also need to have NVIDIA Container Runtime installed.

QSV

For VP9 to work:
- You must have a 9th gen Intel CPU or newer
- If you have an 11th gen CPU or older, then you may need to follow these instructions as Low-Power mode is required
- Additionally, if the server specifically has an 11th gen CPU and is running kernel 5.15 (shipped with Ubuntu 22.04 LTS), then you will need to upgrade this kernel (from Jellyfin docs)

Setup

If you do not already have it, download the latest hwaccel.yml file and ensure it's in the same folder as the docker-compose.yml.
Uncomment the lines that apply to your system and desired usage.
In the docker-compose.yml under immich-microservices, uncomment the lines relating to the hwaccel.yml file.
Redeploy the immich-microservices container with these updated settings.
In the Admin page under FFmpeg settings, change the hardware acceleration setting to the appropriate option and save.

Tips

You may want to choose a slower preset than for software transcoding to maintain quality and efficiency
While you can use VAAPI with Nvidia GPUs and Intel CPUs, prefer the more specific APIs since they're more optimized for their respective devices

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