I think it's interesting that Nvidia is so interested in producing the hardware that fuels the future of software development, given that their primary business advantage is their software moat. This is an interesting project for sure, but turning a bunch of GPUs at Zluda[0] (an open implementation of Cuda) could be far more destructive for them, right?
[0] https://github.com/vosen/ZLUDA
In OpenDLSS: A Vulkan Reimplementation of Nvidia's DLSS 5 Neural Rendering Networkvosen
ZLUDA
Rust2020–2026
vosen / ZLUDA
ZLUDA
CUDA on non-NVIDIA GPUs
48Distinct people
51Mentions
1Explicit recommenders
15.2KGitHub stars
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What it is
CUDA on non-NVIDIA GPUs
GitHub
Where it is used
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From the same repo, I found this excellent, well-written architecture document: https://github.com/vosen/ZLUDA/blob/master/ARCHITECTURE.md I love the direct, "no bullshit"…
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Observed mentions: 2020-11-24 20:09:39 UTC to 2026-10-01 13:04:09 UTC.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
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| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 2 | 2 | 0 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 24 | 0 | 24 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 9 | 1 | 8 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 8 | 1 | 7 |
From the project README
An excerpt from the repository, fetched Nov 13, 2026.
Read the project’s introduction
ZLUDA is a drop-in replacement for CUDA on non-NVIDIA GPUs. ZLUDA allows running unmodified CUDA applications using non-NVIDIA GPUs with near-native performance
Read the full README on GitHubWhat Hacker News says
51 sourcesOh, yikes, I should've checked those links before posting it here. That's certainly not a good look for them.
There was a github repo but I have not checked it.
edit I see, thats an unaffiliated site that latched onto that, my bad, here's the GH that I should've linked: https://github.com/vosen/ZLUDA
In Jeff – Jev-compatible 0.8B decision models, trained at home, ~30 msNo, but we can go there. This is an open source project. Anyone can put some more effort behind it and push it further. It's improving, AFAICS.
Src: https://github.com/vosen/ZLUDA
In CUDA for AMD on WindowsZLUDA – Drop-In Replacement for CUDA on Non-Nvidia GPUs
2 points · Open discussionThere is also ZLUDA, which is open source and works on pre-compiled binaries.
https://github.com/vosen/ZLUDA
In Alternative(s) to run CUDA on non-Nvidia hardwarePerusing the code, the translation seems quite complex.
Shout out to https://github.com/vosen/ZLUDA which is also in this space and quite popular.
I got Zluda to generally work with comfyui well enough.
In BarraCUDA Open-source CUDA compiler targeting AMD GPUsThere is ZLUDA [1] for CUDA, Ollama works on AMD [2], and there's OptiScaler [3] for DLSS. For older AMD GPU there's also FSR 4 INT8, see howto here [4]
[1] https://github.com/vosen/ZLUDA
[2] https://ollama.com/blog/amd-preview https://github.com/likelovewant/ollama-for-amd
[3] https://github.com/optiscaler/OptiScaler
[4] https://github.com/007Lore/AMD-FSR-4-INT8
In Guix System First Impressions as a Nix UserZLUDA was definitely intentional: https://github.com/vosen/ZLUDA/discussions/192
In vLLM large scale serving: DeepSeek 2.2k tok/s/h200 with wide-epThey don't even need to invent anything. Just put in some work to polish what already exists: https://github.com/vosen/ZLUDA
In SoftBank sells its entire stake in NvidiaCould quickly change if open alternatives were suddenly more popular or with stuff like ZLUDA
https://github.com/vosen/ZLUDA
In AMD signs AI chip-supply deal with OpenAI, gives it option to take a 10% stakeI'm pretty sure it's a political limitation, not a technical one. Implementing it is definitely a pain - it's a mix of hardcore backwards compatibility (i.e. cruft) and a rapidly moving target - but it's also obviously just a lot of carefully chosen ascii written down in text files.
The non-nvidia hardware vendors really don't want cuda to win. AMD went for open source + collaborative in a big way, opencl then hsa. Both broadly ignored. I'm not sure what Intel are playing at with spirv - that stack doesn't make any sense to me whatsoever.
Cuda is alright though, in a kind of crufty obfuscation over SSA sense. Way less annoying than opencl certainly. You can run it on amdgpu hardware if you want to - https://docs.scale-lang.com/stable/ and https://github.com/vosen/ZLUDA already exist. I'm hacking on scale these days.
In The race to build a distributed GPU runtimeThere's solutions for that though.
https://docs.scale-lang.com/stable/
https://github.com/vosen/ZLUDA
It's not perfect but it's a start towards unification. In the end though, we're at the same crossroads that graphics drivers were in 2013 with the sunsetting of OpenGL by Apple and the announcement of Vulkan by Khronos Group. CUDA has been around for a while and only recently has it gotten attention from the other chip makers. Thank goodness for open source and the collective minds that participate.
In The Framework Desktop is a beastZLUDA - CUDA on Non-Nvidia GPUs
3 points · Open discussion`I think it also has a way to automatically translate CUDA calls`
I suspect the thing you're referring to is ZLUDA[0], it allows you to run CUDA code on a range of non NVidia hardware (for some value of "run").
[0] https://github.com/vosen/ZLUDA
In Nvidia won, we all lostWhat is the relation between this and Zluda[1]?
[1]https://github.com/vosen/ZLUDA
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