| So there I didn't really follow any blog post or anything, there's a lot of gists about setting it up but they become relatively out of date fairly quickly and are usually specific to their setup. I would checkout:
https://egpu.io/forums/mac-setup/wip-nvidia-egpu-support-for... A lot of people have put in a lot of work to make it as easy as possible to setup. I would just make sure you setup things one at a time and don't immediately jump to trying to get TF or pytorch to work after installing the drivers/ following any sort of guide. Verify your Cuda installation first by building the sample programs and running them. (see http://docs.nvidia.com/cuda/cuda-installation-guide-mac-os-x...) Other than that maybe checkout: https://gist.github.com/jganzabal/8e59e3b0f59642dd0b5f2e4de0...
https://gist.github.com/smitshilu/53cf9ff0fd6cdb64cca69a7e28... The main thing is just getting the GPU drivers setup, after that installing tensorflow requires some modifications to the source (relatively trivial find and replace), and I don't think you have to do anything special for the latest version of pytorch. Other tips: 1. Make sure you're using a thunderbolt 3 cable with whatever egpu you have, other cables will not work even if they're usb c. (USB 3.1 != Thunderbolt 3 != USB C) Read about the differences. 2. I would recommend the AKITO Node enclosure as it seems like most people use it and the community is really small already so if you aren't it might be more difficult to debug issues, but I wouldn't say you couldn't use something else. 3. You'll want to have a docker container that has the CPU version of tensorflow/whatever so you can use that when you don't have the GPU readily available as tensorflow won't work if you installed it with GPU support and your GPU isn't there. 4. If you're trying to use Nvidia-Docker I'm not sure if anyone has gotten that to work on mac because device binding isn't supported on mac for docker. You might be able to get this to work by modifying the docker VM but I'm not sure. |