Linux

48115 readers

690 users here now

From Wikipedia, the free encyclopedia

Linux is a family of open source Unix-like operating systems based on the Linux kernel, an operating system kernel first released on September 17, 1991 by Linus Torvalds. Linux is typically packaged in a Linux distribution (or distro for short).

Distributions include the Linux kernel and supporting system software and libraries, many of which are provided by the GNU Project. Many Linux distributions use the word "Linux" in their name, but the Free Software Foundation uses the name GNU/Linux to emphasize the importance of GNU software, causing some controversy.

Rules

Posts must be relevant to operating systems running the Linux kernel. GNU/Linux or otherwise.
No misinformation
No NSFW content
No hate speech, bigotry, etc

Related Communities

Community icon by Alpár-Etele Méder, licensed under CC BY 3.0

founded 5 years ago

MODERATORS

AgreeableLandscape@lemmy.ml

nooter692@lemmy.ml

MarcellusDrum@lemmy.ml

cypherpunks@lemmy.ml

cyclohexane@lemmy.ml

d3Xt3r@lemmy.nz

Using an AMD GPU for NN training/inference? (lemmy.world)

submitted 1 year ago* (last edited 1 year ago) by leakybits@lemmy.world to c/linux@lemmy.ml

17 comments fedilink hide all child comments

I'm looking to buy a new GPU. My main use case will be training and running neural nets (tensorflow+pytorch); gaming isn't really a priority.

Thing is, I use wayland (via sway), and so I'd really prefer to get an AMD GPU. Nvidia doesn't seem very linux friendly at the moment, especially when it comes to wayland unfortunately.

On the other hand, Nvidia seems to be the clear frontrunner right now when it comes to NN acceleration. I'm worried that if I got an AMD GPU to accelerate my NN work, I'd just be wasting my money.

What do you all think?

Edit: I've used GPUs to accelerate NN models in the past, but they weren't my own, they were provided by my uni's research infra and/or google collab. So this would be the first time I'd be using my own GPU hardware for this purpose.

you are viewing a single comment's thread
view the rest of the comments

[–] ShittyKopper@lemmy.w.on-t.work 9 points 1 year ago* (last edited 1 year ago) (2 children)

Get something new enough and continue getting something new enough when AMD pushes them out. The drivers suck for anything older than an RX580, and things like Blender require even newer GPUs despite the hardware being more than capable.

Run Arch and use the ROCm'd PyTorch from the repos. Those packagers know what they're doing.

Other than that, expect everything premade to be made for CUDA. There are some tools like https://github.com/ROCm-Developer-Tools/HIPIFY but they aren't "there".

Source: Been running Stable Diffusion on an RX580.

[–] leakybits@lemmy.world 2 points 1 year ago (1 children)

Thanks! Sounds doable but definitely frustrating... I'm surprised this is the state of things at the moment. I mean, when you buy a CPU, you don't really think about whether your choice limits you in some ways. But with a GPU, it's a big consideration.

[–] meteokr@community.adiquaints.moe 2 points 1 year ago

Yeah GPUs never got standardized like x86 did from the old IBM machine days. GPUs are still operating on the mindset of "specific hardware" rather than something generic. If GPUs could be programmed on as easily as CPUs we could target something like vulkan for ML.

Even ARM faces similar, but different problems of the lack of standard boot methods.