ocl
Rust-CUDA
ocl | Rust-CUDA | |
---|---|---|
7 | 37 | |
695 | 2,884 | |
1.7% | 2.4% | |
5.9 | 0.0 | |
about 1 month ago | 6 months ago | |
Rust | Rust | |
GNU General Public License v3.0 or later | 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.
ocl
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An example for OpenCL 3.0?
Please note that OpenCL consists of two parts: host API and a separate language which is used to write kernels (code which is going to be offloaded to devices). OpenCL specification describes host APIs as C-style APIs and that is what implementors has to provide. However, there are number of various libraries which provides bindings for other languages: - C++ - Python - Go - Rust
- Any OpenCL + Rust Guides
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Non graphical computing on GPU
ocl
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Resources for Vulkan GPGPU searched
I don't know a lot about Rust, but this looks like a valid set of OpenCL bindings for Rust: https://github.com/cogciprocate/ocl
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What's the current state of GPU compute in rust?
If you prefer an open alternative to CUDA, there are complete, easy to use und well documented bindings for opencl: https://github.com/cogciprocate/ocl/
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Trying to install something using rust and really stuck, any help at all appreciated.
- https://github.com/cogciprocate/ocl/issues/202
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Making an algorithmic trading bot in Rust?
I use Rust with OpenCL (ocl). And I am still in college studying CS. It takes a while to setup OpenCL depending on what you want to do with it. But performance benefits are well worth it. On average I can backtest 4 years of data with 1 minute candles in about 8.745 ms for typical RSI indicator. This is done on i5-3320m CPU (not iGPU). Took me a year to build it. Was also learning rust with it. My project has many features so you probably can do it in half amount of time or even less. Currently the project has 21k in Rust and 2k lines in OpenCL.
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?
nvfancontrol - NVidia dynamic fan control for Linux and Windows
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
wgpu - Cross-platform, safe, pure-rust graphics api.
vuh - Vulkan compute for people
rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations
GLSL - GLSL Shading Language Issue Tracker
CUDA.jl - CUDA programming in Julia.
autograph - Machine Learning Library for Rust
RustaCUDA - Rusty wrapper for the CUDA Driver API
WeasyPrint - The awesome document factory