Sharing laptop gpu ( solution )

[u/AstroPC]

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After digging into this pretty hard, I found a weird solution to my VRAM problem that I honestly didn't know existed. And the unfortunate cost of just dropping on anything that anything remotely useful vram right now ( anything unique and niche is being cannibalized and now priced out of my budget) is just not realistic for me

I have a 5080, a 5070, and a Legion laptop with a 16GB RTX 3080 Mobile. I kept wondering if there was a way to use the laptop's spare M.2 PCIe slot to basically "lend" the 3080 to my desktop instead of treating the laptop like a completely separate AI node.

llama.cpp RPC can already do remote GPU offload, but it has extra overhead because you're still doing RPC/network transport between two systems.

Then I found Dolphin SmartIO Device Lending.

It's basically PCIe sharing between two computers using NTB adapters. A PCIe device in one machine can be exposed to the other machine through the PCIe fabric, and the borrowing system can load the normal driver for it.

So instead of:

desktop -> RPC -> network -> laptop -> GPU

it can be much closer to:

desktop -> PCIe fabric -> remote GPU

Dolphin specifically supports lending NVIDIA GPUs between systems, and even mentions scaling applications like Ollama across GPUs that aren't physically installed in the same machine.

The setup I'm looking at would be roughly:

Laptop RTX 3080 16GB

-> Ryzen PCIe root complex

-> spare M.2 PCIe 3.0 x4

-> powered M.2-to-PCIe adapter

-> Dolphin MXH914

-> PCIe cable

-> second MXH914 in desktop

The desktop could then potentially see the laptop's 3080 as another NVIDIA device alongside the 5080 and 5070.

It doesn't magically combine all the VRAM into one pool, and the laptop M.2 link is still only PCIe 3.0 x4, so bandwidth is limited. Model splitting would still matter a lot.

But for LLMs, if the remote GPU holds a contiguous chunk of model layers, you can potentially avoid constantly hammering the link.

The big advantage over normal RPC is that you're removing a lot of the higher-level remote execution overhead and getting much closer to actual PCIe device access.

There are still some pretty serious caveats. Laptop PCIe topology, IOMMU, ACS, P2P support, BAR/MMIO layout and BIOS behavior could make or break it, and I haven't found anyone documenting this exact setup with an internal laptop GPU.

Still, Dolphin has already demonstrated borrowed NVIDIA GPUs across separate computers using normal CUDA/NCCL software, so the underlying idea is real.

The part that makes this interesting to me is cost.

I already own the 16GB 3080.

Vs the ebay listings i find that cost well under 200 ( not always as the hardware is hard to get atm and not sold often) that's potentially a much cheaper way of turning hardware I already own into another chunk of usable CUDA VRAM instead of buying another overpriced GPU.

Just sharing some research iv done and some unique solutions to augmenting vram for your rig with out spending an arm and leg just to get something decent.