Afaik most LLMs run purely on the GPU, dont they?

So if I have an Nvidia Titan X with 12GB of RAM, could I plug this into my laptop and offload the load?

I am using Fedora, so getting the NVIDIA drivers would be… fun and already probably a dealbreaker (wouldnt want to run proprietary drivers on my daily system).

I know that using ExpressPort adapters people where able to use GPUs externally, and this is possible with thunderbolt too, isnt it?

The question is, how well does this work?

Or would using a small SOC to host a webserver for the interface and do all the computing on the GPU make more sense?

I am curious about the difficulties here, ARM SOC and proprietary drivers? Laptop over USB-c (maybe not thunderbolt?) and a GPU just for the AI tasks…

  • planish@sh.itjust.works
    link
    fedilink
    English
    arrow-up
    4
    ·
    7 months ago

    You’re probably going to run into the problem that people didn’t anticipate your strategy if you try to run a model on a GPU with way more memory than the host system. I’m not sure many execution frameworks can go straight from disk to GPU RAM. Also, storage speed for loading the model might be an issue on an SOC that boots off e.g. an SD card.

    An eGPU dock should do CUDA just as well as an internal GPU, as far as I know. But you would need the drivers installed.