syntaxdot
rust-gpu
syntaxdot | rust-gpu | |
---|---|---|
4 | 82 | |
67 | 6,952 | |
- | 0.8% | |
6.2 | 7.7 | |
6 months ago | 13 days ago | |
Rust | Rust | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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syntaxdot
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Candle: Torch Replacement in Rust
I am so happy about them releasing this. A few years ago I wrote a multi-task syntax annotator in Rust using Laurent Mazare's excellent tch-rs binding (it seems like he is also working on Candle):
https://github.com/tensordot/syntaxdot
However, the deployment story was always quite difficult. The PyTorch C++ API is not stable, so a particular version of tch-rs will only work with a particular PyTorch version. So, anyone wanting to use SyntaxDot always had to get exactly the right version of libtorch (and set some environment variables) to build the project.
The idea of making an abstraction over Torch and Rust ndarray (similar to Burn) crossed my mind several times, but there is only so much that I could do as a solo developer. So Candle would be a god-given if I was still working on this project.
Seeing Candle wants to make me port curated-transformers to Candle for fun:
https://github.com/explosion/curated-transformers
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Ask HN: What is the job market like, for niche languages (Nim, crystal)?
They are obviously not as good as in Python, but if you are willing to invest time, it's definitely doable. E.g. I made a multi-task transformer-based syntax annotator in Rust using the tch Torch binding:
https://github.com/tensordot/syntaxdot
In my current job, I do NLP with Python, Cython, and some C++. I don't think doing it in Rust was much more work. Once you are beyond the stage of implementing a small research project or toy model, most systems are going to contain a lot of custom, specialized code. You will have to do that work in any language.
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PyTorch 1.8 release with AMD ROCm support
What I like about PyTorch is that most of the functionality is actually available through the C++ API as well, which has 'beta API stability' as they call it. So, there are good bindings for some other languages as well. E.g., I have been using the Rust bindings in a larger project [1], and they have been awesome. A precursor to the project was implemented using Tensorflow, which was a world of pain.
Even things like mixed-precision training are fairly easy to do through the API.
[1] https://github.com/tensordot/syntaxdot
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SpaCy v3.0 Released (Python Natural Language Processing)
Huggingface fills the need for task based prediction when you have a GPU.
With model distillation, it should be possible to annotate hundreds of sentences per second on a single CPU with a library like Huggingface Transformers.
For instance, one of my distilled Dutch multi-task syntax models (UD POS, language-specific POS, lemmatization, morphology, dependency parsing) annotates 316 sentences per second with 4 threads on a Ryzen 3700X. This distilled model has virtually no loss in accuracy, compared to the finetuned XLM-RoBERTa base model.
I don't use Huggingface Transformers, but ported some of their implementations to Rust [1], but that should not make a big difference since all the heavy lifting happens in C++ in libtorch anyway.
tl;dr: it is not true that tranformers are only useful for GPU prediction. You can get high CPU prediction speeds with some tricks (distillation, length-based bucketing in batches, etc.).
[1] https://github.com/tensordot/syntaxdot/tree/main/syntaxdot-t...
rust-gpu
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Vcc – The Vulkan Clang Compiler
Sounds cool, but this requires yet another language to learn[0]. As someone who only has limited knowledge in this space, could someone tell me how comparable is the compute functionality of rust-gpu[1], where I can just write rust?
[0] https://github.com/Hugobros3/shady#language-syntax
[1] https://github.com/EmbarkStudios/rust-gpu
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Candle: Torch Replacement in Rust
I don't do anything related to data science, but I feel like doing it in Rust would be nice.
You get operator overloading, so you can have ergonomic matrix operations that are typed also. Processing data on the CPU is fast, and crates like https://github.com/EmbarkStudios/rust-gpu make it very ergonomic to leverage the GPU.
I like this library for creating typed coordinate spaces for graphics programming (https://github.com/servo/euclid), I imagine something similar could be done to create refined types for matrices so you don't do matrix multiplication matrices of invalid sizes
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What's the coolest Rust project you've seen that made you go, 'Wow, I didn't know Rust could do that!'?
Do you mean rust-gpu?
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How a Nerdsnipe Led to a Fast Implementation of Game of Life
And https://github.com/EmbarkStudios/rust-gpu/tree/main/examples with the wgpu runner (here it runs the compute shader)
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What is Rust's potential in game development?
I don't know how major they are considered, but Embark Studios is doing quite a bit of Rust in the open source space, most notably (IMO) rust-gpu and kajiya
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[rust-gpu] How do I run/build my own shaders locally?
The examples in the rust-gpu repository are a good place to start
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Posh: Type-Safe Graphics Programming in Rust
There's another project that's similar that's being used by an actual game company: https://github.com/EmbarkStudios/rust-gpu
They see specific advantages here that would outweigh that negative. It's not my space (I play games, but know next to nothing about graphics programming), but there's at least one argument in the other direction.
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Introducing posh: Type-Safe Graphics Programming in Rust
Could this approach work for compute shaders (GPGPU) as well? So far, I think https://github.com/EmbarkStudios/rust-gpu is the state of the art in that area, but it adds a specific Rust compiler backend for generating SPIR-V rather than leaving that up to the driver. That seems more complicated than it needs to be... but maybe it has advantages too? Thoughts?
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Looking for high level GPU computing crate
https://github.com/embarkstudios/rust-gpu Allows you to create shaders (kernals) in Rust.
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With what languages are video games like League of Legends (most likely) programmed?
Also Embark Studios (formers DICE people) is doing a lot of work with Rust, all open source like Rust GPU https://github.com/EmbarkStudios/rust-gpu
What are some alternatives?
laserembeddings - LASER multilingual sentence embeddings as a pip package
llama.cpp - LLM inference in C/C++
duckling - Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.
wgpu - Cross-platform, safe, pure-rust graphics api.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
Rust-CUDA - Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
projects - 🪐 End-to-end NLP workflows from prototype to production
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
tensorflow - An Open Source Machine Learning Framework for Everyone
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
candle - Minimalist ML framework for Rust
DiligentEngine - A modern cross-platform low-level graphics library and rendering framework