Yes

I dual boot. I’m sure you could get things to work on Windows but it would be a horrible experience.

Most DL hardware accelerator libraries are built and tested to run on servers which are more than likely Linux machines so yeah Linux would be the way to go.

Windows + WSL with Ubuntu is great

yes

I always found this weird. Getting Nvidia drivers to work on Linux is a big pain, yet most ML people use it. I use windows and WSL if I have to. I never go into my Linux dual boot.

I'll extend this: for the majority of real computer science/ engineering work (especially back-end stuff), *nix is the way to go. It's a huge reason Macs are the standard for CS folks (ever since the terminal became part of the MacOS). At every university I attended and taught, and at every company I've worked for, linux/macs have been used by essentially 100% of the people. Roughly once a year I'll hear/see someone using Windows.

Maybe it was a pain years ago, I don't really know but nowadays you just click install nVidia drivers in the software management and it works. There's nothing painful or difficult about it.

Macs for deep-learning?

In my dept a mix of window/Linux. CUDA-GPU fitted machines, mostly TensorFlow /Python. No significant issues with either. But that is, in CS terms quite a limited remit.

Standard driver + cuda. Get yourself a docker container and your good to go 😊 this is probably the easiest way to do it

Nvidia drivers for "simply" compute workloads are really good, just look at all the server with Nvidia GPUs. The problem is when you need to output an image to a screen and deal with Wayland or X11

Is GPU passthrough to WSL/docker working smoothly now?

Just as an ssh box into your linux server

I got TensorFlow 2.0 to work first time on my personal machine on Windows 11 a year ago. I think it has come a long way from before. I just downloaded the latest version of Tensorflow, which was 2.8 at the time, and the CUDA drivers that went with that version, and it all worked nicely.

For research and small projects windows might be bearable, for anything more serious big no

Running VMS / wsl on windows also big no, it's a terrible workaround and completely inefficient, not counting the amount of time to set it up

Does anyone actually use windows on your servers? hows the experience so far?

Yes but WSL is now good enough most of the time, so long as you don't need every last megabyte of VRAM. I'd start with Windows and WSL, and then move to dual boot if you find you need it.

I have not had any problems getting tensorflow to run on windows and utilize my Nvidia gpu. I watched some YT video to get everything setup and the big thing was making sure the versions of all the components were compatible. I’ve also converted my models to onnx and completed inference on windows and Linux (VPS)

You would want to try out Pop OS over Ubuntu for the Linux distro to run on your PC. It makes installation of GPU drivers super easy. Infact you don't even need to do anything. Just select the Nvidia ISO and you should be good to go right after installation!

How do you install the Ubuntu GUI under WSL 2?

Is there a gui for Pop OS or it’s all thru terminal ?

It has a super intuitive and short installation, you just need to select the desired drive and keep pressing next. You can check installation instructions on YouTube too.

You don't, it's essentially access to a Linux 'server' OS that lives in your Windows installation.

You can ssh into it and do almost everything you normally would, except GUIs (QT, KDE, Gnome ...etc)

Actually you can run GUI applications from WSL by installing a windows version of xserv and doing little config within WSL. Check out this guide if you're interested

DL methods are usually using anaconda environments. It should not matter much which os are using as long as you have cuda installed

I've used Windows for a few years. I've had bugs and issues that would never get resolved but all in all it's not a big deal. Tensorflow + C++ + Windows was a nightmare but now I use pytorch->onnx and run onnxruntime in c++ and have no problems.

Haven't tried wsl. I have it setup and I use it to test builds because we are switching to linux at least on the production side so our code compiles for both windows and Linux.

Yeah.. Instead of a no for running on Windows, it would be more likely a no for AMD / Intel GPU. I wonder if there’s any actual working data science shop running on AMD?

Yes it does. Confirmed for nnUnet and Docker also where the GPU follow, i.e WSL-Ubuntu-Docker-GPU

Its only the kernel. If you want GUI I believe you have to go for virtualization

> Windows + WSL with Ubuntu is great

I wouldn't call it "great".

It's very fragile environment compared to running Linux as the host OS. At work our Linux machines have uptimes measure in years, running many jobs 24x7.

It's lucky if my co-worker's GPU-accelerated WSL environments survive a few days.

I much prefer running Linux as the host and Windows in a VM for the rare occasions I need it.

Yes

https://towardsdatascience.com/installing-pytorch-on-apple-m1-chip-with-gpu-acceleration-3351dc44d67c

>> Installing PyTorch on Apple M1 chip with GPU Acceleration

Person is asking for casual non-professional, so maybe good enough? But I agree, pure Linux is better.

Okay cool. I will try this out.

Thanks, I hadn’t seen that implementation, I ran some deep learning models on TensorFlow adapted for iMac GPU, but it was less stable and significantly slower than the Nvidia Linux/Windows equivalents. Things have moved on I guess.

Yes I have a few Macs and do that all the time! …Really I was replying In the context of the OP post however…. setting up a new system for DL.

You can use macs for most toy problems in university too, but otherwise yeah...

Yap

Yes. You can go with Windows but if you don't want to be bothered by your environment and things fo go smoothly take a mainstream Linux distro or something based upon it.

Is it ok to use windows now? I remember 5 years ago I have to install numpy in windows from unofficial repo

Even more recently MS have provided their own solution for Windows 10 (provided you’re running a sufficiently updated version) and 11, which supports both X11 and Wayland.

See here albeit this document is slightly out of date because, as of just a few days ago, they now support Windows 10 from 19.044 (21H2) onwards iirc. Edit: as per here.

Yes. Id say go for an arch based distribution like garuda Linux (perfect for gaming and regular Linux use). Remember never get noveau drivers for your gpu. You can qemu-kvm a windows 10/11 slim etc ISO or just dual boot but it's a Linux machine better just kvm windows.

Garuda kde dragonized btw

Sorry but I also mention arch packages are for bleeding edge tech and garuda isn't for expert Linux users. Better this than Debian distributions even in stability

Yeah it seems to have come a long way. I was prepared for an awful experience based on what others had said, but I found it to be pretty smooth.

Oh shit - this changes everything.... might need to revisit WSL.

Lambda Stack ftw

I think it’s great from a local workstation perspective and see it no more fragile than a standard windows, Mac, or Linux work station environment.

I do agree it doesn’t compare to a professional server cluster. I use wsl at work for a local workstation (small builds/jobs and debugging) but farm out big jobs to a server cluster.

Based on the described use case I think wsl would be a great option. I use it on my personal machine and transitioning from a code/ml project to playing a game of league is so easy compared to switching to my dual boot partition. Running wsl does share system resources with a second os, but the over head of windows is not that large. I personally never run into the case where native Linux provides a Benifit over wsl for jobs small enough that I wouldn’t just farm out to a cloud based server (very rare with my personal projects).

Not exactly answering your question, but a 4090 is probably quite a bit of overkill for personal ml projects. On the rare occasion you will be training models that require those resources, you can probably leverage cloud based resources and it will be cheaper in the long run.

With that said you mentioned gaming being a primary use case of your system. Depending on what you play I assume you will want a windows os, and if that is the case I will echo what others have said and say wsl2 is great.

I personally used a 2070 with wsl 2 for graduate work In computer vision and deep learning.

TIL thanks! Will have to check it out.