gpgpu-rs
Rust-CUDA
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| gpgpu-rs | Rust-CUDA | |
|---|---|---|
| 8 | 37 | |
| 134 | 2,852 | |
| - | 3.8% | |
| 3.8 | 0.0 | |
| 30 days ago | 5 months ago | |
| Rust | Rust | |
| European Union Public License 1.2 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gpgpu-rs
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GPGPU Options
If you don't mind using a pure rust "alternative" you could use wgpu or a wrapper like gpgpu-rs, or any other of the projects mentioned in the other comments.
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Non graphical computing on GPU
gpgpu-rs is a wgpu helper lib
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Compute Shaders and Rust - looking for some guidance.
You could try gpgpu-rs, a compute-focused framework I'm writing. It has some nice integrations with image and ndarray (tho the latter still needs some work) I'll definitely love some feedback :)
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Rust-CUDA: writing and executing extremely fast GPU code fully in Rust
Would be really nice to have an actual cross platform GPGPU library. It's really holding every kind of progress back to have only vendor lock-in.
Maybe WebCPU will be capable of compute to the extend that CUDA isn't necessary. https://github.com/UpsettingBoy/gpgpu-rs
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I was bored so I corrected the corrected calculator by u/pushinat to calculate all possible scenarios between max and lewis. Out of these 3.7 trillion scenarios Max wins 86.6% of them (Fixed fastest lap, and added half points and cancelled races)
gpgpu-rs it is then! 🙂
- gpgpu-rs: A GPGPU compute oriented framework inspired in OpenCL
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Learn Wgpu updated to 0.11
I'm working on a compute framework (gpgpu-rs) based on wgpu, if you wanna check out.
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Is WGSL a good choice?
My recommendation is to stick with WGSL for wgpu. I have some simple compute shaders examples if you wanna check out.
Rust-CUDA
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[Media] Anyone try writing a ray tracer with rust? It's pretty fun!
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)
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Is rust or python better for Machine learning? Or is there enough decent frameworks?
You have this https://github.com/Rust-GPU/Rust-CUDA
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toolchain nightly package building issue
What I'm trying to do is check out https://github.com/Rust-GPU/Rust-CUDA for a class project.
- [Rust] État de GPGPU en 2022
- Which crate for CUDA in Rust?
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Announcing cudarc and fully GPU accelerated dfdx: ergonomic deep learning ENTIRELY in rust, now with CUDA support and tensors with mixed compile and runtime dimensions!
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
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In which circumstances is C++ better than Rust?
- 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
- I learned 7 programming languages so you don't have to
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GNU Octave
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.
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Your average rustafarians
Technically, yes. There are crates for OpenCL and CUDA, although official ROCm support does not exist yet.
What are some alternatives?
wgsl.vim - WGSL syntax highlight for vim
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
wgpu - Cross-platform, safe, pure-rust graphics api.
compute-shader-101 - Sample code for compute shader 101 training
rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations
vange-rs - Rusty Vangers clone
CUDA.jl - CUDA programming in Julia.
GLSL - GLSL Shading Language Issue Tracker
baryon - Fast prototyping 3D engine
WeasyPrint - The awesome document factory