Announcing neuronika 0.1.0, a deep learning framework in Rust

This page summarizes the projects mentioned and recommended in the original post on /r/rust

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  • neuronika

    Tensors and dynamic neural networks in pure Rust.

    Neuronika was developed by a colleague of mine and me for a university project. ( we are master's students in CS). The framework offers auto-differentiation and dynamic neural networks, pretty much like Pytorch does.

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  • are-we-learning-yet

    How ready is Rust for Machine Learning?

    Just make a PR: https://github.com/anowell/are-we-learning-yet

  • juice

    The Hacker's Machine Learning Engine (by fff-rs)

    How does it compare to juice?

  • autograph

    A machine learning library for 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

  • VkFFT

    Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal Fast Fourier Transform library

    The Vulkan docs online are quite good; if i remember they have "hello world" type tutorials as well. An take a look at something like Vulkan fft that has both Vulkan and opencl backends. Looking at "real" projects will of course tens to obscure the main points, but can be helpful for comparison.

  • rust-gpu

    🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧

    there is the rust-gpu effort, an alternative to OpenCL https://github.com/EmbarkStudios/rust-gpu

  • wgpu

    A cross-platform, safe, pure-Rust graphics API.

    It already works pretty well. You can see an example here. I have used it myself quite a bit to do ray tracing and simple matrix calculations. In the linked example the shader uses wgsl, however you can also just use glsl compiled to spirv.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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