About GPU_MEM on RPi4

  • If you are using LE10 then don't worry about them. If you are on LE9.2 you shouldn't worry about them because you'll need to update to LE10 eventually ;)

    From what you said, it looks like it's been resolved in LE10?But When I updated RPI4 to LE10 (LibreELEC-RPi4.arm-9.95.1.img.gz),the same question comes up:

  • If you run LE 10 then leave gpu_mem at the default (76MB). It's only needed for H.264 hardware decoding. Setting it higher just wastes memory.

    so long,

    Hias

  • If you run LE 10 then leave gpu_mem at the default (76MB). It's only needed for H.264 hardware decoding. Setting it higher just wastes memory.

    so long,

    Hias

    Does LE10 dynamically adjust GPU_MEM?Not sure if the video plugin will be used on the GPU (according to the Netflix plugin, it probably won't), so I hope it can be adjusted dynamically.

    In addition, stopping a docker container will cause a LE10 restart. Does this have anything to do with the fact that the GPU_MEM setting is still high?For now, though, the default is still 76.

  • Video decoders and the graphics driver now use CMA memory which can be shared by other (userspace) programs.

    By default we use 512MB CMA, previously we used 384MB but that was not enough to handle all 4k HEVC files. This can be tweaked with the cma dtoverlay - but keep in mind that if you reduce CMA memory you risk running into video decoder / graphics issues.

    No idea about docker, best you open a separate thread about it or discuss in the thread you linked.

    so long,

    Hias

  • Thank you for your professional reply.

    If I do the alignment of the CMA Dtoverlay, where exactly do I do it?The config. TXT?What are the specific command?

  • Yes, /flash/config.txt is the correct place for it. Add a line with eg "dtoverlay=cma,cma-384" at the end of the file to reduce CMA memory size to 384MB. See the README in /flash/overlays for more info about syntax and allowed options.

    so long,

    Hias

  • To provide more context (for posterity & Google Search reasons), the following information might be helpful for providing more of the engineering details & context for why `gpu_mem is no longer as useful for the Raspberry Pi 4 as it was for previous RPi models:

    Source: Raspberry Pi 4 8GB GPU Memory Split - 6by9's post

    Source: Raspberry Pi 4 8GB GPU Memory Split - jamesh's post

    Hopefully this is helpful to surface this information for those interested.