FYI, rust-cuda outputs nvvm so it can integrate with the existing cuda ecosystem. We aren't suggesting rewriting everything in Rust. Check the repo for crates that allow using existing stuff like cudnn and cuBLAS.

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apitman 6 days ago | parent | next [-]

Do you have a link? I went to the rust GPU repo and didn't see anything. I have an academic pipeline that currently heavily tied to CUDA because we need nvCOMP. Eventually we hope us or someone else makes an open source gzip library for GPUs. Until then it would at least be nice if we could implement our other pipeline stages in something more open.

	▲	LegNeato 5 days ago \| parent [-]
		https://github.com/Rust-GPU/Rust-CUDA/tree/main/crates/cudnn and the parent dir has more.

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tucnak 6 days ago | parent | prev [-]

I take it you're the maintainer. Firstly, congrats on the work done, for the open source people are a small crowd, and determination of Rust teams here is commendable. On the other hand, I'm struggling to see the unique value proposition. What is your motivation with Rust-GPU? Graphics or general-purpose computing? If it's the latter, at least from my POV, I would struggle to justify going up against a daunting umbrella project like this; in view of it likely culminating in layers upon layers of abstraction. Is the long-term goal here to have fun writing a bit of Rust, or upsetting the entrenched status quo of highly-concurrent GPU programming? There's a saying that goes along like "pleasing all is a lot like pleasing none," and intuitively I would guess it should apply here.

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LegNeato 6 days ago | parent [-]

Thanks! I'm personally focused on compute, while other contributors are focused on graphics.

I believe GPUs are the future of computing. I think the tooling, languages, and ecosystems of GPUs are very bad compared to CPUs. Partially because they are newer, partially because they are different, and partially because for some reason the expectations are so low. So I intend to upset the status quo.

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tucnak 6 days ago | parent [-]

Have you considered post-GPU accelerators? For large-scale machine learning, TPU's have won, basically. There are new vendors like Tenstorrent offering completely new (and much simpler) computing hardware. GPU's may as well live on borrowed time as far as compute is concerned.

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LegNeato 5 days ago | parent [-]

Yes, see the proposed WG link I posted above. When I say GPU I'm using it as shorthand...indeed, I think the "graphics" part is on borrowed time and will just become fully software. It is already happening.

	▲	tucnak 5 days ago \| parent [-]
		Tenstorrent is often criticised for having lots of abstraction layers, compilers, IR's in the middle—it's all in C++, of course. GPU's are okay, but none of them got network-on-chip capability. Some promising papers have been coming out, like SystolicAttention, etc. There's just so much stuff for GPU's, but not that much for sysolic NoC systems (TPU, TT, NPU's) I think Rust could really make an impact here. Abandon all GPU deadweight, stick to simple abstractions, assume 3d twisted torus for topology and that's it. Food for thought!