Diffractor.jl vs oxide-enzyme

Diffractor.jl

Next-generation AD (by JuliaDiff)

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oxide-enzyme

Enzyme integration into Rust. Experimental, do not use. (by EnzymeAD)

Rust auto-differentiation Ad Enzyme Gradient derivative

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Diffractor.jl		oxide-enzyme
	Project
3	Mentions	4
425	Stars	102
0.0%	Growth	-
9.2	Activity	2.9
25 days ago	Latest Commit	about 1 year ago
Julia	Language	Rust
MIT License	License	Apache License 2.0

The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

Diffractor.jl

Posts with mentions or reviews of Diffractor.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-30.

Julia 1.7 has been released
15 projects | news.ycombinator.com | 30 Nov 2021
Diffractor.jl – Next Generation Automatic Differentiation
1 project | news.ycombinator.com | 15 Aug 2021
Next-Generation Automatic Differentiation (Ad) in Julia
1 project | news.ycombinator.com | 24 Jul 2021

oxide-enzyme

Posts with mentions or reviews of oxide-enzyme. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-11.

Enzyme: towards state-of-the-art AutoDiff in Rust
2 projects | /r/rust | 11 Dec 2021

Afterwards, you can have a look at https://github.com/rust-ml/oxide-enzyme, where I published some toy examples. The current approach has a lot of limitations, mostly due to using the ffi / c-abi to link the generated functions. @bytesnake and I are already looking at an alternative implementation which should solve most, if not all issues. For the meantime, we hope that this already helps those who want to do some early testing. This link might also help you to understand the Rust frontend a bit better. I will add a larger blog post once oxide-enzyme is ready to be published on crates.io.
Oxide-Enzyme: Integrating LLVM's Static Automatic Differentiation Plugin
1 project | /r/rust4quants | 30 Nov 2021

3 projects | /r/rust | 30 Nov 2021
Julia 1.7 has been released
15 projects | news.ycombinator.com | 30 Nov 2021

What are some alternatives?

When comparing Diffractor.jl and oxide-enzyme you can also consider the following projects:

JuliaInterpreter.jl - Interpreter for Julia code

DiffEqOperators.jl - Linear operators for discretizations of differential equations and scientific machine learning (SciML)

SciMLBenchmarks.jl - Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

Enzyme - High-performance automatic differentiation of LLVM and MLIR.

RecursiveFactorization.jl

mujoco - Multi-Joint dynamics with Contact. A general purpose physics simulator.

ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

Infiltrator.jl - No-overhead breakpoints in Julia

FrechetDiff.jl - FrechetDiff is an experimental Julia package for automatic differentiation (AD).

DifferentialEquations.jl - Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.