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I put together a linux box with a 2080ti a few years ago and have been using it consistently for personal ml research ever since. Ive found it well worth the in
by jdeaton 5y ago
I put together a linux box with a 2080ti a few years ago and have been using it consistently for personal ml research ever since. Ive found it well worth the investment and learned that the ease with which I can jump into hacking on a project is key, which is why this works so well for me. I can just ssh in at any time and start experimenting with models. Even if its not technically economical when you do the math, the ease, reliability and fact that I know my models arent being billed per hour helps encourage me to experiment often, which is kwy to learning.
As for software, I do everything with jax and tensorboard for viewing experiments. Jax is a phenomenal library for personal ml learning as its extremely flexible and has relatively low level composable abstractions.
- anonymousDan 5y agoWhat do you wrt CUDA and linux? I'm a linux person but every time I try and mess around with CUDA the whole thing gets super annoying. I don't want to have to reinstall everything every time there is a kernel upgrade . Maybe there is some trick with WSL2 now?
- mark_l_watson 5y agoI can’t speak to using WSL2 on Windows, but on my Linux System76 GPU laptop I get around CUDA configuration time sinks by not updating my configuration for long periods of time. I don’t mind spending setup time once every 6 months, but I don’t want to waste my time during it frequently. System76 has new container oriented CUDA setup that is OK, but I liked just setting everything up on my own, and then not modifying anything for as long as possible.