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Cuda (feddit.de)
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[-] Gabu@lemmy.ml 74 points 9 months ago* (last edited 9 months ago)

I prefer ROCM:
R -
O -
C -
M -

  • Fuck me, it didn't work again
[-] MustrumR@kbin.social 40 points 9 months ago

I program 2-3 layers above (Tensorflow) and those words reverberate all the way up.

[-] Bipta@kbin.social 20 points 9 months ago

I program and those words reverberate.

[-] Pyroglyph@lemmy.world 14 points 9 months ago
[-] Scew@lemmy.world 8 points 9 months ago
[-] stingpie@lemmy.world 7 points 9 months ago

Recently, I've just given up trying to use cuda for machine learning. Instead, I've been using (relatively) cpu intensive activation functions & architecture to make up the difference. It hasn't worked, but I can at least consistently inch forward.

[-] Thcdenton@lemmy.world 38 points 9 months ago

Oh cool I got the wrong nvidia driver installed. Guess I'll reinstall linux 🙃

[-] corsicanguppy@lemmy.ca 5 points 9 months ago

Yum downgrade.

[-] GammaGames@beehaw.org 18 points 9 months ago

Related to D: today vscode released an update that made it so you can’t use the remote tools with Ubuntu 18.04 (which is supported with security updates until 2028) 🥴 the only fix is to downgrade

[-] Uranium3006@kbin.social 16 points 9 months ago

Some numbnut pushed nvidia driver code with compilation errors and now I have to use an old Kernel until it's fixed

[-] baltakatei@sopuli.xyz 15 points 9 months ago

Nvidia: I have altered the deal, pray I do not alter it further.

[-] avidamoeba@lemmy.ca 11 points 9 months ago

Not a hot dog.

[-] observantTrapezium@lemmy.ca 8 points 9 months ago

I've been working with CUDA for 10 years and I don't feel it's that bad...

[-] scrion@lemmy.world 12 points 9 months ago

I started working with CUDA at version 3 (so maybe around 2010?) and it was definitely more than rough around the edges at that time. Nah, honestly, it was a nightmare - I discovered bugs and deviations from the documented behavior on a daily basis. That kept up for a few releases, although I'll mention that NVIDIA was/is really motivated to push CUDA for general purpose computing and thus the support was top notch - still was in no way pleasant to work with.

That being said, our previous implementation was using OpenGL and did in fact produce computational results as a byproduct of rendering noise on a lab screen, so there's that.

[-] Skullgrid@lemmy.world 2 points 9 months ago

I don't know wtf cuda is, but the sentiment is pretty universal: please just fucking work I want to kill myself

[-] topinambour_rex@lemmy.world 3 points 9 months ago

Cuda turns a gpu in to a very fast cpu for specific operations. It won't replace the cpu, just assist it.

Graphics are just maths. Plenty of operations for display the beautiful 3d models with the beautiful lights and shadows and shines.

Those maths used for display 3d, can be used for calculate other stuffs, like chatgpt's engine.

[-] sprack@lemmy.world 8 points 9 months ago

Pretty much the exact reason containerized environments were created.

[-] theterrasque@infosec.pub 3 points 9 months ago

Yep, I usually make docker environments for cuda workloads because of these things. Much more reliable

[-] tias@discuss.tchncs.de 2 points 9 months ago* (last edited 9 months ago)

You can't run a different Nvidia driver in a container though

[-] sprack@lemmy.world 1 points 9 months ago

When you hit that config need the next step is light weight VM + pcie passthru.

[-] Justas@sh.itjust.works 8 points 9 months ago

I don't know what any of this means, upvoted everything anyway.

[-] Presi300@lemmy.world 2 points 9 months ago* (last edited 9 months ago)

Insert JavaScript joke here

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this post was submitted on 01 Feb 2024
530 points (95.7% liked)

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