[nextos]

> APL could work well with gpus

I've seen at least an APL implementation running on top of Julia, thanks to macros.

Julia has good GPU support, and it makes it easy to compose that support with any library.

However, kdb+ and q, which are APL descendants, have good GPU support already: https://code.kx.com/q/interfaces/gpus. But licenses are not cheap...

[koolala]

GPUs can even run APL as a higher level programming language. It's the only abstract language I've ever heard to run on a GPU. Arrays in, Arrays out. A gpu is array programming hardware.

I hope one day its normal like the 1000s of CPU languages. Would be nice to have more than 10 gpu languages.

[LegNeato]

Check out https://github.com/Rust-GPU/rust-gpu if you have not seen it

[pjmlp]

StarLisp on the Connection Machine, which is kind of early attempt to what GPU became.

Futhark is another more recent example.

[twoodfin]

CM-Lisp was closer to that vision, though it was never (TMK) fully implemented, unlike StarLisp.

https://dl.acm.org/doi/pdf/10.1145/319838.319870

[anonzzzies]

There is the famous '17 line' compiler here https://scholarworks.iu.edu/dspace/items/3ab772c9-92c9-4f59-...

(I got the t-shirt)

[pistoleer]

That's a phd dissertation with hundreds of pages, wrong link maybe?

[abrudz]

No, it appears on page 210 (logical page 220).

[anonzzzies]

Thanks, I forgot to add that!

[Athas]

This looks like an invocation of a C++ CUDA kernel through an FFI. It is not running k or q directly on the GPU.