Enzyme VS bevy

Automatic differentiation is done using https://enzyme.mit.edu/

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

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.

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.

Have you taken a look at enzymeAD? There is a group porting it to rust.

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.

Idk, Enzyme is pretty next gen, all the way down to LLVM code.

https://github.com/EnzymeAD/Enzyme

I'm working on merging my build-tool for (oxide)-enzyme into Enzyme itself. Also looking into improving the documentation.

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.

Bevy. A very young engine where you need to write the game entirely in Rust—that was appealing. But fatal flaws overshadowed everything: no editor, the engine brutally enforces the ECS approach, and the game's architecture must literally bend to fit this paradigm. So, you won't migrate to another engine at all—you just throw away all the code and start from scratch.

Missing one of the best choices as long as "maturity" isn't on the top of your list: Bevy - https://bevyengine.org/

Game engine written in Rust, leveraging ECS in almost every place and way, with a really capable WASM export option. Wrestling ECS for the first time might take you some time, but in my experience helps you keep game code as clean and decoupled as game code could be.

I don't see WASM/WebGPU changing anything when it comes to gaming, as an industry, personally. 3d visualizations and interactive websites? Yeah definitely a nice improvement over WebGL 2, if years late.

WebGPU is pretty far behind what AAA games are using even as of 6 years ago. There's extra overhead and security in the WebGPU spec that AAA games do not want. Browsers do not lend themselves to downloading 300gb of assets.

Additionally, indie devs aren't using Steam for the technical capabilities. It's purely about marketshare. Video games are a highly saturated market. The users are all on Steam, getting their recommendations from Steam, and buying games in Steam sales. Hence all the indie developers publish to Steam. I don't see a web browser being appealing as a platform, because there's no way for developers to advertise to users.

That's also only indie games. AAA games use their own launchers, because they don't _need_ the discoverability from being on Steam. So they don't, and avoid the fees. If anything users _want_ the Steam monopoly, because they like the platform, and hate the walled garden launchers from AAA companies.

(I work on high end rendering features for the Bevy game engine https://bevyengine.org, and have extensive experience with WebGPU)

I was working through an example in the repo for the Bevy game engine recently and came across this code

That's possible. I did spend quite a bit of time tinkering with compiler flags, and followed the recommendations.

Some notes I found just now seems to agree with my results, though: https://github.com/bevyengine/bevy/issues/3978#issuecomment-...

I cannot recommend immediate mode GUI programming based on the limitations I've experienced working with egui.

egui does not support putting two widgets in the center of the screen: https://github.com/emilk/egui/issues/3211

It's really easy to get started with immediate mode, it's really easy to bust out some UI, but the second you start trying to involve dynamically resized context and responsive layouts -- abandon all hope. The fact it has to calculate everything in a single pass makes these things hard/impossible.

... that said, I'm still using it for https://ant.care/ (https://github.com/MeoMix/symbiants) because it's the best thing I've found. I'm crossing my fingers that Bevy's UI story (or Kayak https://github.com/StarArawn/kayak_ui) become significantly more fleshed out sooner rather than later. Bevy 0.13 should have lots more in this area though (https://github.com/bevyengine/bevy/discussions/9538)

I've also been enjoying building My First Game™ in Bevy using ECS. The community around Bevy really shines, but Flecs (https://github.com/SanderMertens/flecs) is arguably a more mature, open-source ECS implementation. You don't get to write in Rust, though, which makes it less cool in my book :)

I'm not very proud of the code I've written because I've found writing a game to be much more confusing than building websites + backends, but, as the author notes, it certainly feels more elegant than OOP or globals given the context.

I'm building for WASM and Bevy's parallelism isn't supported in that context (yet? https://github.com/bevyengine/bevy/issues/4078), so the performance wins are just so-so. Sharing a thread with UI rendering suuucks.

If anyone wants to browse some code or ask questions, feel free! https://github.com/MeoMix/symbiants

These days, some game engines have done pretty well at making compute shaders easy to use (such as Bevy [1] -- disclaimer, I contribute to that engine). But telling the scientific/financial/etc. community that they need to run their code inside a game engine to get a decent experience is a hard sell. It's not a great situation compared to how easy it is on NVIDIA's stack.

[1]: https://github.com/bevyengine/bevy/blob/main/examples/shader...

This is the API you need: https://github.com/bevyengine/bevy/pull/9774