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I mean, my entry deep learning machine was a refurbished Linux box with a pile of gpus I found in the electronics recycling bin at work. Later upgraded to a 108
by sdenton4 6y ago
I mean, my entry deep learning machine was a refurbished Linux box with a pile of gpus I found in the electronics recycling bin at work. Later upgraded to a 1080 and then a 2080, as one does.
The nice thing about the desktop is that it can just train for days and I don't need to work about using it for other things, losing time moving locations, etc. It's also still probably cheaper than the m1 laptop, even with a nicer gpu than what you can find in the trash.
- coredog64 6y agoI did the same (well, used a discarded GPU that my kids didn't need any more) and I have one caution: If you're using PyTorch, you'll want to have a CPU that at least supports AVX. The C++ libraries that ship with PyTorch assume AVX at compile time and don't have an option to disable at runtime. It's a PITA to recompile the entire stack.
- p1esk 6y agoNot sure what you are talking about. Pytorch binaries don’t assume anything about your CPU.