If you’re using Metal to run your llms, you may have noticed the amount of VRAM available is around 60%-70% of the total RAM - despite Apple’s unique architecture for sharing the same high-speed RAM between CPU and GPU.

It turns out this VRAM allocation can be controlled at runtime using sudo sysctl iogpu.wired_limit_mb=12345

See here: https://github.com/ggerganov/llama.cpp/discussions/2182#discussioncomment-7698315

Previously, it was believed this could only be done with a kernel patch - and that required disabling a macos security feature … And tbh that wasn’t that great.

Will this make your system less stable? Probably. The OS will need some RAM - and if you allocate 100% to VRAM, I predict you’ll encounter a hard lockup, spinning Beachball, or just a system reset. So be careful to not get carried away. Even so, many will be able to get a few more gigs this way, enabling a slightly larger quant, longer context, or maybe even the next level up in parameter size. Enjoy!

  • bebopkim1372@alien.topB
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    1 year ago

    Maybe 47536MB is the net model size. For LLM inference, memory for context and optional context cache memory are also needed.