TensorFlow.jl
Vulkan.jl
| TensorFlow.jl | Vulkan.jl | |
|---|---|---|
| 1 | 2 | |
| 879 | 106 | |
| - | 0.0% | |
| 0.0 | 8.0 | |
| almost 3 years ago | 4 months ago | |
| Julia | Julia | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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TensorFlow.jl
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Flux vs. TensorFlow
My understanding is that Tensorflow.jl does not wrap the Python library, but the underlying C implementation. So it was an alternative to the Python version, not just a wrapper of it, and this gave it some advantages: https://github.com/malmaud/TensorFlow.jl/blob/master/docs/src/why_julia.md
Vulkan.jl
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GPU vendor-agnostic fluid dynamics solver in Julia
You may be confusing front end APIs and the compiler backends.
Julia is flexible enough that you can essentially define domain specific languages within Julia for certain applications. In this case, we are using Julia as an abstract front end and then deferring the concrete interface to vendor specific GPU compilation drivers. Part of what permits this is that Julia is a LLVM front end and many of the vendor drivers include LLVM-based backends. With some transformation of the Julia abstract syntax tree and the LLVM IR we can connect the two.
That said we are mostly dependent on vendors providing the backend compiler technology. When they do, we can bridge Julia to use that interface. We can wrap Vulkan and technologies like oneAPI.
https://github.com/JuliaGPU/Vulkan.jl
- Cuda.jl v3.3: union types, debug info, graph APIs
What are some alternatives?
Zygote.jl - 21st century AD
oneAPI.jl - Julia support for the oneAPI programming toolkit.
julia - The Julia Programming Language
AMDGPU.jl - AMD GPU (ROCm) programming in Julia
FastAI.jl - Repository of best practices for deep learning in Julia, inspired by fastai
GPUCompiler.jl - Reusable compiler infrastructure for Julia GPU backends.
FiniteDiff.jl - Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
Metal.jl - Metal programming in Julia
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
MLJ.jl - A Julia machine learning framework
www.julialang.org - Julia Project website