Having a bit of trouble getting hardware acceleration working on my home server. The cpu of the server is an i7-10700 and has a discrete GPU, RTX 2060. I was hoping to use intel quick sync for the hardware acceleration, but not having much luck.
From the guide on the jellyfin site https://jellyfin.org/docs/general/administration/hardware-acceleration/intel
I have gotten the render group ID using “getent group render | cut -d: -f3” though it mentions on some systems it might not be render, it may be video or input which i tried with those group ID’s as well.
When I run “docker exec -it jellyfin /usr/lib/jellyfin-ffmpeg/vainfo” I get back
libva info: VA-API version 1.22.0
libva info: Trying to open /usr/lib/jellyfin-ffmpeg/lib/dri/nvidia_drv_video.so
libva info: Trying to open /usr/lib/x86_64-linux-gnu/dri/nvidia_drv_video.so
libva info: Trying to open /usr/lib/dri/nvidia_drv_video.so
libva info: Trying to open /usr/local/lib/dri/nvidia_drv_video.so
libva info: va_openDriver() returns -1
vaInitialize failed with error code -1 (unknown libva error),exit
I feel like I need to do something on the host system since its trying to use the discrete card? But I am unsure.
This is the compose file just in case I am missing something
version: "3.8"
services:
jellyfin:
image: jellyfin/jellyfin
user: 1000:1000
ports:
- 8096:8096
group_add:
- "989" # Change this to match your "render" host group id and remove this comment
- "985"
- "994"
# network_mode: 'host'
volumes:
- /home/hoxbug/Docker/jellyfin/config:/config
- /home/hoxbug/Docker/jellyfin/cache:/cache
- /mnt/External/Movies:/Movies
devices:
- /dev/dri/renderD128:/dev/dri/renderD128
networks:
external:
external: true
Thank you for the help.
Isn’t your GPU an Nvidia RTX 2060? Why are you trying to use the Intel GPU acceleration method? I’m confused
It just seemed the easiest route, but I may just give using the GPU a go.
From personal experience intel QSV wasn’t worth the trouble to txshoot on my hardware. Mine is a lot older than yours though. Vaapi has worked well on my arc card
QSV is the highest quality video transcoding hardware acceleration out there. It’s worth using if you have a modern Intel CPU (8th gen or newer)
This is how mine works, with a Nvidia GPU
services: jellyfin: volumes: - jellyfin_config:/config - jellyfin_cache:/cache - type: tmpfs target: /cache/transcodes tmpfs: size: 8G - media:/media image: jellyfin/jellyfin:latest restart: unless-stopped deploy: resources: reservations: devices: - driver: nvidia device_ids: - "0" capabilities: - gpu
What is the tmpfs for?
Temp files for transcoding. No need to hit the disk.