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.

  • Saiwal
    140·
    25 days ago

    On my system i was able to use my integrated iGPU wit the follwing:

        devices:     - /dev/dri:/dev/dri

    The rest of your compose looks fine.

  • SneezycatEnglish
    101·
    25 days ago

    Isn’t your GPU an Nvidia RTX 2060? Why are you trying to use the Intel GPU acceleration method? I’m confused

    • hoxbugOPEnglish
      20·
      25 days ago

      It just seemed the easiest route, but I may just give using the GPU a go.

      • __ghost__English
        20·
        25 days ago

        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

        • entropicdriftEnglish
          80·
          25 days ago

          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)

  • bobslaedeEnglish
    50·
    25 days ago

    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
      • bobslaedeEnglish
        80·
        25 days ago

        Temp files for transcoding. No need to hit the disk.

          • 486English
            20·
            24 days ago

            It is. It might end up on disk in swap, if you run low on memory (and have some sort of disk-based swap enabled), but usually it is located in RAM.

            • __ghost__English
              10·
              24 days ago23 days ago

              You can create a tmpfs on other storage devices as well, just curious what their setup looked like

              • 486English
                10·
                22 days ago22 days ago

                No, tmpfs is always located in virtual memory. Have a look at the kernel documentation for more information about tmpfs.

          • bobslaedeEnglish
            10·
            25 days ago

            Hmm. I would think so. But I haven’t actually checked. That was my thought.

  • entropicdriftEnglish
    10·
    25 days ago25 days ago

    If you switch the devices line to

    - /dev/dri:/dev/dri

    as other have suggested, that should expose the Intel iGPU to your Jellyfin docker container. Presently you’re only exposing the Nvidia GPU.

  • JustEnoughDucksEnglish
    10·
    24 days ago

    Do you have the Intel drivers installed on your machine? Are GuC and HuC working?

    sudo reboot
sudo dmesg | grep i915
sudo cat /sys/kernel/debug/dri/0/gt/uc/guc_info
sudo cat /sys/kernel/debug/dri/0/gt/uc/huc_info

    On Debian I had to manually download the i915 full driver Zip, extract it, take out the Intel drivers, and put it in /usr/lib/firmware

    Then hardware acceleration worked on my Arc380.

    If you use QSV, your CPU iGPU will be the one that can use it, so make sure to set your render device in docker to the iGPU and not the RTX 2060

  • HumanPersonEnglish
    10·
    25 days ago25 days ago

    I have an arc for transcoding, and I had to set the device to /dev/dri without the renderD128 part. If I were you, I would just use the 2060. If it’s there for llama or something I’d still try it and see how it does doing both at once, as it should be separate parts of the gpu handling that.