this post was submitted on 09 Apr 2025
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The problem is simple: consumer motherboards don't have that many PCIe slots, and consumer CPUs don't have enough lanes to run 3+ GPUs at full PCIe gen 3 or gen 4 speeds.

My idea was to buy 3-4 computers for cheap, slot a GPU into each of them and use 4 of them in tandem. I imagine this will require some sort of agent running on each node which will be connected through a 10Gbe network. I can get a 10Gbe network running for this project.

Does Ollama or any other local AI project support this? Getting a server motherboard with CPU is going to get expensive very quickly, but this would be a great alternative.

Thanks

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[–] vane@lemmy.world 4 points 1 year ago* (last edited 1 year ago) (1 children)

If you want to use supercomputer software, setup SLURM scheduler on those machines. There are many tutorials how to do distributed gpu computing with slurm. I have it on my todo list.
https://github.com/SchedMD/slurm
https://slurm.schedmd.com/

[–] marauding_gibberish142@lemmy.dbzer0.com 1 points 1 year ago (1 children)

Thanks but I'm not going to run supercomputers. I just want to run 4 GPUs separately because of inadequate PCIe lanes in a single computer to run 24B-30B models

[–] vane@lemmy.world 1 points 1 year ago* (last edited 1 year ago) (1 children)

I believe you can run 30B models on single used rtx 3090 24GB at least I run 32B deepseek-r1 on it using ollama. Just make sure you have enought ram > 24GB.

[–] marauding_gibberish142@lemmy.dbzer0.com 1 points 1 year ago (1 children)
[–] vane@lemmy.world 1 points 1 year ago* (last edited 1 year ago) (1 children)

I run this one. https://ollama.com/library/deepseek-r1:32b-qwen-distill-q4_K_M with this frontend https://github.com/open-webui/open-webui on single rtx 3090 hardware 64gb ram. It works quite well for what I wanted it to do. I wanted to connect 2x 3090 cards with slurm to run 70b models but haven't found time to do it.