>A will to live (optional but recommended)
>LLVM is NOT required. BarraCUDA does its own instruction encoding like an adult.
>Open an issue if theres anything you want to discuss. Or don't. I'm not your mum.
>Based in New Zealand
Oceania sense of humor is like no other haha
The project owner strongly emphasize the no LLM dependency, in a world of AI slope this is so refreshing.
The cheer amount of knowledge required to even start such project, is really something else, and prove the manual wrong on the machine language level is something else entirely.
When it comes to AMD, "no CUDA support" is the biggest "excuse" to join NVIDIA's walled garden.
Godspeed to this project, the more competition the less NVIDIA can continue destroying the PC parts pricing.
The project owner is talking about LLVM,a compiler toolkit, not an LLM.
Very few total number of commits, AI like documentation and code comments.
But even if LLMs were used, the overall project does feel steered by a human, given some decisions like not using bloated build systems. If this actually works then that's great.
Don't care though. AI can work wonders in skilled hands and I'm looking forward to using this project
I do use LLM's (specifically Ollama) particularly for test summarisation, writing up some boilerplate and also I've used Claude/Chatgpt on the web when my free tier allows. It's good for when I hit problems such as AMD SOP prefixes being different than I expected.
Reminded me of the beached whale animated shorts[1].
[1]: https://www.youtube.com/watch?v=ezJG0QrkCTA&list=PLeKsajfbDp...
> The project owner strongly emphasize the no LLM dependency, in a world of AI slope this is so refreshing.
"Has tech literacy deserted the tech insider websites of silicon valley? I will not beleove it is so. ARE THERE NO TRUE ENGINEERS AMONG YOU?!"
I'll be the party pooper here, I guess. The manual is still right, and no amount of reverse-engineering will fix the architecture AMD chose for their silicon. It's absolutely possible to implement a subset of CUDA features on a raster GPU, but we've been doing that since OpenCL and CUDA is still king.
The best thing the industry can do is converge on a GPGPU compute standard that doesn't suck. But Intel, AMD and Apple are all at-odds with one another so CUDA's hedged bet on industry hostility will keep paying dividends.
What sucks is that such projects at some point become too big, and make so much noise forcing big techs to buy them and everybody gets fuck all.
All it requires to beat proprietary walled garden, is somebody with knowledge and a will to make things happen. Linus with git and Linux is the perfect example of it.
Fun fact, BitKeeper said fuck you to the Linux community in 2005, Linus created git within 10 days.
BitKeeper make their code opensource in 2016 but by them, nobody knew who they were lol
So give it time :)
Supporting CUDA on AMD would only build a bigger moat for NVidia; there's no reason to cede the entire GPU programming environment to a competitor and indeed, this was a good gamble; as time goes on CUDA has become less and less essential or relevant.
Also, if you want a practical path towards drop-in replacing CUDA, you want ZLUDA; this project is interesting and kind of cool but the limitation to a C subset and no replacement libraries (BLAS, DNN, etc.) makes it not particularly useful in comparison.
When it comes to GPUs, AMD just has the vibe of a company that basically shrugged and gave up. It's a shame because some competition would be amazing in this environment.
More like wouldn't* most of the time.
Well isn't that the case with a few other things? FSR4 on older cards is one example right now. AMD still won't officially support it. I think they will though. Too much negativity around it. Half the posts on r/AMD are people complaining about it.
They're working the problem, but slandering them over it isn't going to make it come out any faster.
It works fine.
> They're working the problem, but slandering them over it isn't going to make it come out any faster.
You have insider info everyone else doesn't? They haven't said any such thing yet last I checked. If that were true, they should have said that.
Open-source projects are being inundated with PR from AIs, not depending on them doesn't limit a project.
That project owner seems pretty knowledgeable of what is going on and keeping it free of dependencies is not an easy skill. Many developers would have written the code with tons of dependency and copy/paste from LLM. Some call the later coding :)
If your needs can be expressed as tensor operations or neural network stuff that tinygrad supports, might as well use that (or one of the ten billion other higher order tensor libs).
Seeing insane investments (in time/effort/knowledge/frustration) like this make me enjoy HN!!
(And there is always the hope that someone at AMD will see this and actually pay you to develop the thing.. Who knows)
Write CUDA code. Run Everywhere. Your CUDA skills are now universal. SCALE compiles your unmodified applications to run natively on any accelerator, ending the nightmare of maintaining multiple codebases.