bootloader VS Rust-CUDA

That's just an unbased claims. People have written bootloader in rust and the linux kernel is also considering adopting Rust. None of this would happen if Rust cannot interface the hardware or is turing complete.

The "official" (with outdated code) bootloader: https://github.com/rust-osdev/bootloader/blob/main/src/bin/uefi.rs

A quick wander through the docs, and then the repo turned up an open feature request for VESA video modes which mentions a merged PR for 320x200 VGA support.

But here I come across an interesting structure https://github.com/rust-osdev/bootloader/tree/main/examples/test_framework

Long story short, it appears there is no way to get started with UEFI (cue more downvotes). I've even spent a week carefully copying code beginning here: https://github.com/rust-osdev/bootloader/blob/main/src/bin/uefi.rs only to discover that nothing displays to the screen. There is an error somewhere in the 500 lines required to print a character to the screen, and it's impossible to tell where it is.

rust-osdev/bootloader

You can also take a look at the upcoming version of the bootloader crate, which has UEFI support: https://github.com/rust-osdev/bootloader/pull/130 . It is not documented very well yet, but maybe it helps already. The UEFI entry point function is here .The #[entry] macro of the uefi crate just makes the function a pub extern "efiapi" fn. The function is named efi_main because that's the default entry point name for Rust's built-in UEFI targets (e.g. x86_64-unknown-uefi). Theimageandst` function arguments are passed directly by the UEFI firmware.

Source code [here](https://github.com/ihawn/RTracer) if anyone is interested in taking a look or giving feedback. As a side question, does anyone have any general advise on getting GPU compute working with rust? I tried [this project](https://github.com/Rust-GPU/Rust-CUDA) but had a bunch of issues (And it doesn't look like an active repo anyways)

You have this https://github.com/Rust-GPU/Rust-CUDA

What I'm trying to do is check out https://github.com/Rust-GPU/Rust-CUDA for a class project.

Be warned, NON_BLOCKING streams do not fully synchronize with sync host to device copies. They are not guaranteed to actually finish by the time they return. Meaning its possible to initiate a copy, then initiate a kernel launch, and have the copy be unfinished by the time the kernel is launched. This caused so many confusing bugs that i personally decided to stop using NON_BLOCKING altogether in rust-cuda. https://github.com/Rust-GPU/Rust-CUDA/issues/15

- Cuda is not doing by FFI linking, instead is compiling CUDA code natively in Rust https://github.com/Rust-GPU/Rust-CUDA and even if it not complete as the C++ SDK is more than a toy

Given your criteria, you might want to consider (modern) C++.

* Fast - in many cases faster than Rust, although the difference is inconsequential relative to Python-to-Rust improvement I guess.

* _Really_ utilize CUDA, OpenCL, Vulcan etc. Specifically, Rust GPU is limited in its supported features, see: https://github.com/Rust-GPU/Rust-CUDA/blob/master/guide/src/... ...

* Host-side use of CUDA is at least as nice, and probably nicer, than what you'll get with Rust. That is, provided you use my own Modern C++ wrappers for the CUDA APIs: https://github.com/eyalroz/cuda-api-wrappers/ :-) ... sorry for the shameless self-plug.

* ... which brings me to another point: Richer offering of libraries for various needs than Rust, for you to possibly utilize.

* Easier to share than Rust. A target system is less likely to have an appropriate version of Rust and the surrounding ecosystem.

There are downsides, of course, but I was just applying your criteria.

Technically, yes. There are crates for OpenCL and CUDA, although official ROCm support does not exist yet.