this post was submitted on 01 Feb 2024
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Programmer Humor

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[–] Gabu@lemmy.ml 67 points 1 year ago* (last edited 1 year ago)

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

  • Fuck me, it didn't work again
[–] MustrumR@kbin.social 37 points 1 year ago (2 children)

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

[–] Bipta@kbin.social 19 points 1 year ago (1 children)

I program and those words reverberate.

[–] Pyroglyph@lemmy.world 14 points 1 year ago (1 children)
[–] Scew@lemmy.world 8 points 1 year ago
[–] stingpie@lemmy.world 7 points 1 year 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 34 points 1 year ago (1 children)

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

[–] corsicanguppy@lemmy.ca 4 points 1 year ago

Yum downgrade.

[–] GammaGames@beehaw.org 19 points 1 year ago (1 children)

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

[–] baltakatei@sopuli.xyz 12 points 1 year ago

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

[–] Uranium3006@kbin.social 12 points 1 year ago

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

[–] sprack@lemmy.world 8 points 1 year ago (1 children)

Pretty much the exact reason containerized environments were created.

[–] theterrasque 3 points 1 year ago (1 children)

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

[–] tias@discuss.tchncs.de 2 points 1 year ago* (last edited 1 year ago) (1 children)

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

[–] sprack@lemmy.world 1 points 1 year ago

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

[–] avidamoeba@lemmy.ca 8 points 1 year ago

Not a hot dog.

[–] observantTrapezium@lemmy.ca 5 points 1 year ago (2 children)

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

[–] scrion@lemmy.world 9 points 1 year 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 1 year ago (1 children)

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 1 year 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.

[–] Justas@sh.itjust.works -1 points 1 year ago

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