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Comment by brrrrrm | Hacker News Reader

It's worth noting that these pre-built blocks are both convenient and incredibly flexible. Before I started getting my hands dirty, it was hard to really see this. For example, here's a masked gather operation along the innermost dimension of an arbitrary rank tensor A:

    A[..., idx[mask]]

I'd hate to have to express that in serial code and then pray a compiler could lift the correct vectorized version out of it.

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Sure, but any language can provide that kind of pre-built block in a library. (Indeed, I suspect the library we're discussing has this operation, though I didn't check.) But if you want to implement a new operation that performs well, not every language can do that. In python, people tend to drop down to C or C++ or increasingly Rust to do that. But it seems (to me) like it would be nice to be able to use a single language for both things.

At least with the more common modern ML (LLMs etc) operations, no one drops down to Rust. It's really only good for IO/CPU work, but that's rarely a spot for new operations, just for data loading and high-latency network stuff.

People typically use Triton or CUDA (usually the C++ flavor) to implement operations. It'd be cool if Rust had a CUDA dialect.

The point is that someone dropped down to implement those operations, at some point.

It seems like you can target CUDA with Rust, because this project seems to be doing that?

https://github.com/huggingface/candle/blob/main/candle-kerne...

That’s the C++ variant of cuda, not Rust. They’re just binding it as one might in Python. At which point, what’s the value add?

Aha! Thanks for digging that up!

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