Rust-CUDA VS naga

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.

That wouldn't have been all that different from WGSL though, the most important thing is that whatever WebGPU uses for its shaders can be translated to and from SPRIV (and WGSL does that too (e.g. via https://dawn.googlesource.com/tint and https://github.com/gfx-rs/naga).

Hey all, wanted to put this link in here, where I'm proposing changing the API for errors in naga, so Naga can take ownership of error presentation and actually Make Shader Compilation Messages Comfy™: https://github.com/gfx-rs/naga/issues/2317

EDIT: There is also naga but it does not take HLSL as input: https://github.com/gfx-rs/naga but you can use DirectXShaderCompiler to compile to SpirV, then use naga to compile to Metal.

And it seems that naga https://github.com/gfx-rs/naga Already has a working front/backend for wgsl.

This is basically Ray Tracing support in Blade. So far, only ray queries are supported. Unlike prior work on ray tracing in Rust, this is original due to all shader code being WGSL, see the Naga PR.

There's a compiler that can translate from WGSL to SPIR-V called naga. Having such a compiler is essential, since WebGPU is planned to use WGSL and browsers are expected to implement rendering via Vulkan (and probably Metal and DX12).

Not sure about on the CPU, but naga is a shading language transpiler you can write custom front/backends for.

The spec docs are actually pretty useful https://www.w3.org/TR/WGSL/ besides that I was using naga's tests for reference https://github.com/gfx-rs/naga/tree/master/tests

For cross-platform support look at WebGPU and Vulkan (e.g,: [0] [1]. Essentially, you would need to write the func in WGSL or GLSL, HLSL or MSL. Each of these can be cross-compiled to SPIR-V (what Vulkan needs) with cross-compilers such as spirv-cross and naga.