compute-shader-101
gpgpu-rs
compute-shader-101 | gpgpu-rs | |
---|---|---|
8 | 8 | |
489 | 135 | |
2.7% | - | |
0.0 | 3.8 | |
3 months ago | about 1 month ago | |
Rust | Rust | |
Apache License 2.0 | European Union Public License 1.2 |
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.
compute-shader-101
-
wgpu-rs resources for computing purposes only
You might find compute shader 101 useful.
- Vulkan terms vs. Direct3D 12 (aka DirectX 12) terms
-
WGPU setup and compute shader feedback - and Tutorial.
Compute Shader 101 - Github, Video, Slideshow. additional resources at end of slide show.
-
Compute Shaders and Rust - looking for some guidance.
Yes, compute-shader-101 is sample code + video + slides.
-
Prefix sum on portable compute shaders
Workgroup in Vulkan/WebGPU lingo is equivalent to "thread block" in CUDA speak; see [1] for a decoder ring.
> Using atomics to solve this is rarely a good idea, atomics will make things go slowly, and there is often a way to restructure the problem so that you can let threads read data from a previous dispatch, and break your pipeline into more dispatches if necessary.
This depends on the exact workload, but I disagree. A multiple dispatch solution to prefix sum requires reading the input at least twice, while decoupled look-back is single pass. That's a 1.5x difference if you're memory saturated, which is a good assumption here.
The Nanite talk (which I linked) showed a very similar result, for very similar reasons. They have a multi-dispatch approach to their adaptive LOD resolver, and it's about 25% slower than the one that uses atomics to manage the job queue.
Thus, I think we can solidly conclud that atomics are an essential part of the toolkit for GPU compute.
You do make an important distinction between runtime and development environment, and I should fix that, but there's still a point to be made. Most people doing machine learning work need a dev environment (or use Colab), even if they're theoretically just consuming GPU code that other people wrote. And if you do distribute a CUDA binary, it only runs on Nvidia. By contrast, my stuff is a 20-second "cargo build" and you can write your own GPU code with very minimal additional setup.
[1]: https://github.com/googlefonts/compute-shader-101/blob/main/...
-
Compute shaders - where to learn more outside of unity
googlefonts/compute-shader-101: Sample code for compute shader 101 training (github.com)
-
Vulkan Memory Allocator
I agree strongly with you about the need for good resources. Here are a few I've found that are useful.
* A trip through the Graphics Pipeline[1] is slightly dated (10 years old) but still very relevant.
* If you're interested in compute shaders specifically, I've put together "compute shader 101"
* Alyssa Rosenzweig's posts[3] on reverse engineering GPUs casts a lot of light on how they work at a low level. It helps to have a big-picture understanding first.
I think there is demand for a good book on this topic.
[1]: https://fgiesen.wordpress.com/2011/07/09/a-trip-through-the-...
[2]: https://github.com/googlefonts/compute-shader-101
[3]: https://rosenzweig.io/
-
Compute shader 101 (video and slides)
This is a talk I've been working on for a while. It starts off motivating why you might want to write compute shaders (tl;dr you can exploit the impressive compute power of GPUs but portably), then explains the basics of how, including some sample code to help get people started.
Slides: https://docs.google.com/presentation/d/1dVSXORW6JurLUcx5UhE1...
Sample code: https://github.com/googlefonts/compute-shader-101
Feedback is welcome (please file issues against the open source repo), and AMA in this thread.
gpgpu-rs
-
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.
-
Non graphical computing on GPU
gpgpu-rs is a wgpu helper lib
-
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 :)
-
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
-
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
-
Learn Wgpu updated to 0.11
I'm working on a compute framework (gpgpu-rs) based on wgpu, if you wanna check out.
-
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.
What are some alternatives?
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
wgsl.vim - WGSL syntax highlight for vim
raylib - A simple and easy-to-use library to enjoy videogames programming
wgpu - Cross-platform, safe, pure-rust graphics api.
emscripten - Emscripten: An LLVM-to-WebAssembly Compiler
Rust-CUDA - Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
strange-attractors
vange-rs - Rusty Vangers clone
vello - An experimental GPU compute-centric 2D renderer.
Vulkan-Guide - One stop shop for getting started with the Vulkan API
baryon - Fast prototyping 3D engine