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Did you build a machine with 4x 3090 ? I looking for a way to build such a machine for ML training.

I did! I started by going to vast.ai. I was able to look at the specs of the top-scoring machines. I started with the motherboard (as I knew it could support my 3090s, because some PCIe busses can't handle all that data). Then of course I copied everything else that I could. I ended up using PCIe extenders and zip-tieing (plastic, I should use metal zip ties instead) the cards to a rack I got from Lowes. I'm not too pleased with how it looks, but it works!

BTW, depending on where you're at in your ML journey, Jeremy Howard from FastAI says you should focus more on using hosted instances like paperspace until you really need to get your own machine. Unless, of course, you enjoy linux sysadmin tasks. :) It can get really annoying trying to match the right version of CUDA with the version of Pytorch you're trying to get running for the newest model you're trying.

Here are the parts I can find CPU: https://www.newegg.com/amd-epyc-7252-socket-sp3/p/N82E168191... Motherboard: https://www.newegg.com/asrock-rack-romed8-2t/p/N82E168131400... SSD: https://www.newegg.com/samsung-2tb-980-pro/p/N82E16820147796... Computer Power Supply (the GPUs have their own power supplies, run apart from the computer, which I'm told is bad, but... seems to work for years now for me): https://www.newegg.com/corsair-hx-series-hx1200-cp-9020140-n... PCIe 4.0 x16 Risers: https://www.newegg.com/p/N82E16812987068?Item=N82E1681298706... Tower: https://www.newegg.com/black-fractal-design-meshify-2-compac... RAM: https://www.newegg.com/nemix-ram-16gb-288-pin-ddr4-sdram/p/1...

Total, without GPUs and their power supplies: $2900

Thanks man! Super helpful.

Wondering the same here

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