This should eventually make it’s way into jellyfin. Eager to see the performance improvements.

  • @[email protected]
    link
    fedilink
    English
    377 months ago

    As far as I’m aware this is only for the cli version of ffmpeg and won’t affect the threading of codecs many of which were already multithreaded.

    • @Lmaydev
      link
      English
      77 months ago

      It’s literally for the CLI yeah.

    • @[email protected]
      link
      fedilink
      English
      27 months ago

      I recently tried figuring out how to build ffmpeg with Nvidia codecs. I’m very new to ffmpeg and codec terminology. How is multithreading for the CLI different than the codecs?

      • @[email protected]
        link
        fedilink
        English
        77 months ago

        My understanding is some parts have to be done sequentially even though the parts themselves are multithreaded, now the different parts can all be done in parallel.

      • @Lmaydev
        link
        English
        1
        edit-2
        6 months ago

        Change the main loop and every component (demuxers, decoders, filters, encoders, muxers) to use the previously added transcode scheduler.

        The components are what they have parallelised.

  • AutoTL;DRB
    link
    fedilink
    English
    47 months ago

    This is the best summary I could come up with:


    The long-in-development work for a fully-functional multi-threaded FFmpeg command line has been merged!

    FFmpeg is widely-used throughout many industries for video transcoding and in today’s many-core world this is a terrific improvement for this key open-source project.

    The patches include adding the thread-aware transcode scheduling infrastructure, moving encoding to a separate thread, and various other low-level changes.

    Change the main loop and every component (demuxers, decoders, filters, encoders, muxers) to use the previously added transcode scheduler.

    There’s a recent presentation on this work by developer Anton Khirnov.

    It’s terrific seeing this merged and will be interesting to see the performance impact in practice.


    The original article contains 226 words, the summary contains 103 words. Saved 54%. I’m a bot and I’m open source!