Enzyme
xstate
Our great sponsors
Enzyme | xstate | |
---|---|---|
16 | 60 | |
1,153 | 26,119 | |
3.0% | 1.3% | |
9.6 | 9.6 | |
7 days ago | 6 days ago | |
LLVM | TypeScript | |
GNU General Public License v3.0 or later | MIT License |
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.
Enzyme
-
Show HN: Curve Fitting Bezier Curves in WASM with Enzyme Ad
Automatic differentiation is done using https://enzyme.mit.edu/
-
Ask HN: What Happened to TensorFlow Swift
lattner left google and was the primary reason they chose swift, so they lost interest.
if you're asking from an ML perspective, i believe the original motivation was to incorporate automatic differentiation in the swift compiler. i believe enzyme is the spiritual successor.
https://github.com/EnzymeAD/Enzyme
-
Show HN: Port of OpenAI's Whisper model in C/C++
https://ispc.github.io/ispc.html
For the auto-differentiation when I need performance or memory, I currently use tapenade ( http://tapenade.inria.fr:8080/tapenade/index.jsp ) and/or manually written gradient when I need to fuse some kernel, but Enzyme ( https://enzyme.mit.edu/ ) is also very promising.
MPI for parallelization across machines.
-
Do you consider making a physics engine (for RL) worth it?
For autodiff, we are currently working again on publishing a new Enzyme (https://enzyme.mit.edu) Frontend for Rust which can also handle pure Rust types, first version should be done in ~ a week.
-
What is a really cool thing you would want to write in Rust but don't have enough time, energy or bravery for?
Have you taken a look at enzymeAD? There is a group porting it to rust.
-
The Julia language has a number of correctness flaws
Enzyme dev here, so take everything I say as being a bit biased:
While, by design Enzyme is able to run very fast by operating within the compiler (see https://proceedings.neurips.cc/paper/2020/file/9332c513ef44b... for details) -- it aggressively prioritizes correctness. Of course that doesn't mean that there aren't bugs (we're only human and its a large codebase [https://github.com/EnzymeAD/Enzyme], especially if you're trying out newly-added features).
Notably, this is where the current rough edges for Julia users are -- Enzyme will throw an error saying it couldn't prove correctness, rather than running (there is a flag for "making a best guess, but that's off by default"). The exception to this is garbage collection, for which you can either run a static analysis, or stick to the "officially supported" subset of Julia that Enzyme specifies.
Incidentally, this is also where being a cross-language tool is really nice -- namely we can see edge cases/bug reports from any LLVM-based language (C/C++, Fortran, Swift, Rust, Python, Julia, etc). So far the biggest code we've handled (and verified correctness for) was O(1million) lines of LLVM from some C++ template hell.
I will also add that while I absolutely love (and will do everything I can to support) Enzyme being used throughout arbitrary Julia code: in addition to exposing a nice user-facing interface for custom rules in the Enzyme Julia bindings like Chris mentioned, some Julia-specific features (such as full garbage collection support) also need handling in Enzyme.jl, before Enzyme can be considered an "all Julia AD" framework. We are of course working on all of these things (and the more the merrier), but there's only a finite amount of time in the day. [^]
[^] Incidentally, this is in contrast to say C++/Fortran/Swift/etc, where Enzyme has much closer to whole-language coverage than Julia -- this isn't anything against GC/Julia/etc, but we just have things on our todo list.
-
Jax vs. Julia (Vs PyTorch)
Idk, Enzyme is pretty next gen, all the way down to LLVM code.
https://github.com/EnzymeAD/Enzyme
-
What's everyone working on this week (7/2022)?
I'm working on merging my build-tool for (oxide)-enzyme into Enzyme itself. Also looking into improving the documentation.
- Wsmoses/Enzyme: High-performance automatic differentiation of LLVM
-
Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia
that seems one of the points of enzyme[1], which was mentioned in the article.
[1] - https://enzyme.mit.edu/
being able in effect do interprocedural cross language analysis seems awesome.
xstate
-
Mastering XState Fundamentals: A React-powered Guide
XState is a powerful library with comprehensive documentation. Keeping the documentation handy while building your next app with XState will be invaluable.
- 5 Alternatives to Redux for React State Management
-
Unleashing the Power of Actors in Frontend Application Development
XState is an excellent library that simplifies the utilization of actors in JavaScript applications. While this article focuses on using React, these principles apply equally well to other frameworks. In fact, they can be implemented anywhere JavaScript is executed.
-
Rethinking State Management - Why XState is a Game-Changer for Developers
In this article, I want to share a personal journey of discovery in the world of state management. My path led me to XState, a tool that I believe is the best choice for managing state in modern applications like React, Angular, Vue, and others. This isn't just a professional advice; it's a personal recommendation based on real-world experience.
-
Get out of state management hell with automatic revalidation
You add the current user state to a React Context or state management library, read from it on the top bar, and write to it after a user signs in. Done. No big deal, right?
- Como encontrar tema de tcc em ciência da computação?
- Sequence diagrams, the only good thing UML brought to software development
-
Scalability: the Lost Level of React State Management
Lastly, I know that I've omitted many great tools like XState, React Query, and SWR. These tools are utilities that are very scalable in their own right, but aren't full replacements for a good state manager.
- JavaScript State Machines and Statecharts
What are some alternatives?
Zygote.jl - 21st century AD
redux - A JS library for predictable global state management
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
jssm - Fast, easy Javascript finite state machines with visualizations; enjoy a one liner FSM instead of pages. MIT; Typescripted; 100% test coverage. Implements the FSL language.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
ringpop-go - Scalable, fault-tolerant application-layer sharding for Go applications
Lux.jl - Explicitly Parameterized Neural Networks in Julia
downshift 🏎 - 🏎 A set of primitives to build simple, flexible, WAI-ARIA compliant React autocomplete, combobox or select dropdown components.
linfa - A Rust machine learning framework.
zustand - 🐻 Bear necessities for state management in React
faust - Functional programming language for signal processing and sound synthesis
awesome-workflow-engines - A curated list of awesome open source workflow engines