Not familiar with CUDA development, but doesn't CUDA support C++ ? Skipping Clang/LLVM and going "pure" C seems to be quite limiting in that case.
h4kunamata | 2026-02-17 23:07 UTC
Real developer never depended on AI to write good quality code, in fact, the amount of slope code flying left and right is due to LLM.
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 :)
gsora | 2026-02-17 23:13 UTC
LLVM and LLM are not the same thing
brookman64k | 2026-02-17 23:17 UTC
LLVM (Low Level Virtual Machine) != LLM (Large Language Model)
hackyhacky | 2026-02-17 23:33 UTC
Honestly I'm not sure how good is LLVM's support for AMD GX11 machine code. It's a pretty niche backend. Even if it exists, it may not produce ideal output. And it's a huge dependency.
bri3d | 2026-02-18 02:03 UTC
Quite good, it’s first party supported by AMD (ROCm LLVM, with a lot upstreamed as well) where it’s fairly widely used in production.
This project is a super cool hobby/toy project but ZLUDA is the “right” drop in CUDA replacement for almost any practical use case.
phoronixrly | 2026-02-17 22:08 UTC
Putting a registered trademark in your project's name is quite a brave choice. I hope they don't get a c&d letter when they get traction...
cadamsdotcom | 2026-02-17 22:21 UTC
Maybe a rename to Barra. Everyone will still get the pun :)
I wonder if they could change the name to Barracuda if pressed. The capitalization is all that keeps it from being a normal English word, right?
sam_goody | 2026-02-17 22:24 UTC
Wow!! Congrats to you on launch!
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)
piker | 2026-02-17 22:28 UTC
> # It's C99. It builds with gcc. There are no dependencies.
> make
Beautiful.
parlortricks | 2026-02-17 23:57 UTC
You gotta love it, simple and straight to the point.
esafak | 2026-02-17 22:36 UTC
Wouldn't it funny and sad if a bunch of enthusiasts pulled off what AMD couldn't :)
h4kunamata | 2026-02-17 23:02 UTC
Many projects turned out to be far better than proprietary because open-source doesn't have to please shareholders.
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 :)
bri3d | 2026-02-17 23:24 UTC
The lack of CUDA support on AMD is absolutely not that AMD "couldn't" (although I certainly won't deny that their software has generally been lacking), it's clearly a strategic decision.
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.
enlyth | 2026-02-18 00:07 UTC
Even disregarding CUDA, NVidia has had like 80% of the gaming market for years without any signs of this budging any time soon.
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.
fdefitte | 2026-02-18 00:28 UTC
Agreed on ZLUDA being the practical choice. This project is more impressive as a "build a GPU compiler from scratch" exercise than as something you'd actually use for ML workloads. The custom instruction encoding without LLVM is genuinely cool though, even if the C subset limitation makes it a non-starter for most real CUDA codebases.
wmf | 2026-02-17 23:26 UTC
We have HIP at home.
guerrilla | 2026-02-17 23:41 UTC
> couldn't
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.
DiabloD3 | 2026-02-17 23:46 UTC
Because FSR4 is currently slower on RDNA3 due to lack of support of FP8 in hardware, and switching to FP16 makes it almost as slow as native rendering in a lot of cases.
They're working the problem, but slandering them over it isn't going to make it come out any faster.
bravetraveler | 2026-02-17 22:36 UTC
> No HIP translation layer.
Storage capacity everywhere rejoices
h4kunamata | 2026-02-17 22:49 UTC
>Requirements
>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.
querez | 2026-02-17 22:59 UTC
> The project owner strongly emphasize the no LLM dependency, in a world of AI slope this is so refreshing.
The project owner is talking about LLVM,a compiler toolkit, not an LLM.
kmaitreys | 2026-02-18 00:08 UTC
It's actually quite easy to spot if LLMs were used or not.
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.
wild_egg | 2026-02-17 23:28 UTC
This project very most definitely has significant AI contributions.
Don't care though. AI can work wonders in skilled hands and I'm looking forward to using this project
ZaneHam | 2026-02-18 00:11 UTC
Hello! I didn't realise my project was posted here but I can actually answer this.
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.
bigyabai | 2026-02-17 23:40 UTC
> and prove the manual wrong on the machine language level
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.
magicalhippo | 2026-02-17 23:47 UTC
> Oceania sense of humor is like no other haha
Reminded me of the beached whale animated shorts[1].
> >LLVM is NOT required. BarraCUDA does its own instruction encoding like an adult.
> 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?!"
dboreham | 2026-02-18 01:03 UTC
Unrelated: just returned from a month in NZ. Amazing people.
colordrops | 2026-02-18 01:03 UTC
I'm still blown away that AMD hasn't made it their top priority. I've said this for years. If I was AMD I would spend billions upon billions if necessary to make a CUDA compatibility layer for AMD. It would certainly still pay off, and it almost certainly wouldn't cost that much.
andy_ppp | 2026-02-18 01:09 UTC
Moving target, honestly just get PyTorch working fully (loads of stuff just doesn’t work on AMD hardware) and also make it work on all graphics cards from a certain generation. The matrix of support needed GFX cards, architectures and software together is quite astounding but still yes that should have at least that working and equivalent custom kernels.
ddtaylor | 2026-02-18 01:41 UTC
AMD did hire someone to do this and IIRC he did, but they were afraid of Nvidia lawyers and he released it outside of the company?
ekianjo | 2026-02-18 01:30 UTC
LLVM, nothing to do with LLMs
yodon | 2026-02-17 22:59 UTC
<checks stock market activity>
gclawes | 2026-02-17 23:15 UTC
What's the benefit of this over tinygrad?
bri3d | 2026-02-17 23:21 UTC
Completely different layer; tinygrad is a library for performing specific math ops (tensor, nn), this is a compiler for general CUDA C code.
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).
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.
Comments
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 :)
This project is a super cool hobby/toy project but ZLUDA is the “right” drop in CUDA replacement for almost any practical use case.
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)
> make
Beautiful.
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.
Storage capacity everywhere rejoices
>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.
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.
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?!"
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).
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.