[rvz]

This is a bit good for Rust if you want to use the language with CUDA. The problem is, it still doesn't really move the needle if you really don't like running closed source drivers and runtime binaries and care about open source.

Continuing from this discussion [0], this only makes it a Rust or a CUDA problem rather than a Python, CUDA and a PyTorch one if there bug in one of them.

Yet at the end of the day, it still uses Nvidia's closed source CUDA compiler 'nvcc' which they will never open source. A least Mojo promises to open source their own compiler which compiles to different accelerators with multiple backend support.

Unlike this...but uses Rust.

[0] https://news.ycombinator.com/item?id=48067228

[the__alchemist]

IMO this has nothing to do with open source as an ideology; just a practical (and official?) lib for adding GPU interaction to your rust programs.

[nihalpasham]

Small correction: cuda-oxide does not use `nvcc` to compile Rust kernels.

The device path is roughly: rustc frontend/MIR -> cuda-oxide’s Pliron-based IR/lowering pipeline -> LLVM IR -> PTX via LLVM’s NVPTX backend. Host code still goes through normal rustc/LLVM codegen.

You still need the NVIDIA driver/toolkit pieces to run CUDA code and load PTX on NVIDIA GPUs, so this does not change the broader CUDA ecosystem/dependency story. But it is not “Rust source handed to nvcc”; it is a Rust compiler backend generating device code.

[bigyabai]

> it still doesn't really move the needle if you really don't like running closed source drivers and runtime binaries

Those people probably did not buy an Nvidia GPU for themselves. It should be common knowledge that the "Open" Nvidia drivers still run gigantic firmware blobs to dispatch complex workloads. And Nouveau is close to useless for GPGPU compute.

[charcircuit]

Considering how fast everything is changing with GPUs and how competitive it is. It doesn't make sense to have an open source driver.

[pjmlp]

Mojo remains to be seen if it isn't another Swift for Tensorflow, apparently 1.0 won't even support Windows properly.

[zamalek]

My sentiment matches your exactly. I'm sick and tired of CUDA - but it's really not going to change.

Could maybe be forked with some dynamic smarts, HIP is basically 1:1 with CUDA: https://github.com/amd/amd-lab-notes/blob/release/hipify%2Fs...

[pjmlp]

Does it support a graphical GPU debugging for C++, Fortran and Python JIT GPU code?

Otherwise it isn't 1:1 with CUDA, and I am not counting everything else on CUDA ecosystem

[zamalek]

Debugging (gdb, but GUI frontends exist for gdb in general): https://rocm.docs.amd.com/projects/HIP/en/latest/how-to/debu...

Fortran: https://github.com/ROCm/hipfort

Python (not sure about JIT): https://rocm.docs.amd.com/projects/hip-python/en/latest/

[pjmlp]

All those are far from the 1:1 CUDA experience.