this post was submitted on 16 Mar 2024
261 points (74.0% liked)
linuxmemes
21581 readers
1195 users here now
Hint: :q!
Sister communities:
Community rules (click to expand)
1. Follow the site-wide rules
- Instance-wide TOS: https://legal.lemmy.world/tos/
- Lemmy code of conduct: https://join-lemmy.org/docs/code_of_conduct.html
2. Be civil
- Understand the difference between a joke and an insult.
- Do not harrass or attack members of the community for any reason.
- Leave remarks of "peasantry" to the PCMR community. If you dislike an OS/service/application, attack the thing you dislike, not the individuals who use it. Some people may not have a choice.
- Bigotry will not be tolerated.
- These rules are somewhat loosened when the subject is a public figure. Still, do not attack their person or incite harrassment.
3. Post Linux-related content
- Including Unix and BSD.
- Non-Linux content is acceptable as long as it makes a reference to Linux. For example, the poorly made mockery of
sudo
in Windows. - No porn. Even if you watch it on a Linux machine.
4. No recent reposts
- Everybody uses Arch btw, can't quit Vim, and wants to interject for a moment. You can stop now.
Please report posts and comments that break these rules!
Important: never execute code or follow advice that you don't understand or can't verify, especially here. The word of the day is credibility. This is a meme community -- even the most helpful comments might just be shitposts that can damage your system. Be aware, be smart, don't fork-bomb your computer.
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Earlier in my career, I compiled tensorflow with CUDA/cuDNN (NVIDIA) in one container and then in another machine and container compiled with ROCm (AMD) for cancerous tissue detection in computer vision tasks. GPU acceleration in training the model was significantly more performant with NVIDIA libraries.
It's not like you can't train deep neural networks without NVIDIA, but their deep learning libraries combined with tensor cores in Turing-era GPUs and later make things much faster.
AMD is catching up now. There are still performance differences, but they are probably not as big in the latest generation.
Things have changed.
I can now run mistral on my intel iGPU using Vulkan.
If you're talking about "running", that's inference. I'm talking about elapsed training time.
Same thing. Inference just uses a lot less memory.