autograph
are-we-learning-yet
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autograph | are-we-learning-yet | |
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5 | 5 | |
299 | 422 | |
- | - | |
9.2 | 4.9 | |
24 days ago | 8 days ago | |
Rust | Rust | |
Apache License 2.0 | Creative Commons Attribution 4.0 |
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.
autograph
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Where to Learn Vulkan for parallel computation (with references to porting from CUDA)
I'm working on a machine learning library https://github.com/charles-r-earp/autograph implemented in Rust that uses rust-gpu to compile Rust compute shaders to spirv, and then gfx_hal to target metal and dx12. Training performance is currently about 2x slower than pytorch (cuda) on my laptop but I've made significant progress recently and I am targeting 1.5x. While rust-gpu itself has it's own restrictions, it does support inline spirv assembly, which provides direct access to operations not provided in its std lib, thus it's lower level than GLSL. For example, it should be possible to target cuda tensor cores via cooperative matrix operations (I believe Metal supports these as well but this may not be implemented in spirv-cross and certainly isn't in naga). Once I have things a bit more stabilized I'd like to provide more examples, like porting from cuda / opencl, but I'm still figuring out patterns like how to work with 16 and 8 bit types in a nice and portable way.
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autograph v0.1.0
autograph v0.1.0
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What's the current state of GPU compute in rust?
Working on autograph, for machine learning and neural networks. Unlike CUDA / HIP it's threadsafe, but doesn't expose low level things like multiple streams. Most of the shaders are glsl but I'm now using rust_gpu for pure rust gpu code.
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Announcing neuronika 0.1.0, a deep learning framework in Rust
Maybe not for learning but as inspiration I have to plug this amazing effort for ML with (vulkan) shaders: https://github.com/charles-r-earp/autograph
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What do you think about a library that helps reducing the overhead of GPU programming, regarding ndimensional Arrays?
Maybe you'd be interested in checking out my library, https://github.com/charles-r-earp/autograph?
are-we-learning-yet
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This year I tried solving AoC using Rust, here are my impressions coming from Python!
Also http://arewelearningyet.com
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[D] Is Rust stable/mature enough to be used for production ML? Is making Rust-based python wrappers a good choice for performance heavy uses and internal ML dependencies in 2021?
Hey OP, you might want to check this site out: http://arewelearningyet.com
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Is rust good for mathematical computing?
Note that you can update the page (adding packages or updating descriptions) via those github issues: https://github.com/anowell/are-we-learning-yet/issues
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I wanted to share my experience of Rust as a deep learning researcher
Not sure if you’ve encountered it, but you should be aware of http://arewelearningyet.com
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Announcing neuronika 0.1.0, a deep learning framework in Rust
Just make a PR: https://github.com/anowell/are-we-learning-yet
What are some alternatives?
neuronika - Tensors and dynamic neural networks in pure Rust.
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
RustaCUDA - Rusty wrapper for the CUDA Driver API
petgraph - Graph data structure library for Rust.
wgpu - Cross-platform, safe, pure-rust graphics api.
book - The Rust Programming Language
VkFFT - Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal Fast Fourier Transform library
rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
juice - The Hacker's Machine Learning Engine
Awesome-Rust-MachineLearning - This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, etc. 🦀