I love finding hacky ways to save money on hardware, but unfortunately NVidia is just too good at the game and the 170HX was destined for the landfill at birth. God forbid a few of us enthusiasts get A100 performance for under a grand.

The next best thing is a 3090 or the like with a broken PCIe power connector or some other minor defect. My 3090 is simply missing the bit that holds the clip of the power connector in, however it’s a snug fit anyway and with the cables crammed into my case as they are, I don’t think it’s going anywhere. I paid $200 less than market for that 3090 as a result. Less than a gram of plastic. $200 off.

Meanwhile, as the article points out, AMD is nowhere near as hostile towards its customer base, and modified Radeon cards can apparently be had for $100 or so (from China). The caveat of course is no CUDA support, so it’s kind of moot.

There is some CUDA support on AMD. I'm using it on a daily basis, it's much more production ready than you would expect. Do you use pytorch or something else?

How do you have “some” CUDA support? I’m aware of the AMD HIP API that ports CUDA code to run on AMD GPUs, but that’s not CUDA at that point. Im also aware of the geohot (George Hotz) project for bringing native CUDA to AMD GPUs, but I think he abandoned it because AMD wasn’t throwing him any bones.

Cupy on Python is mostly what I use.

This is what they are referring to: https://github.com/ROCm-Developer-Tools/HIPIFY