Box2D VS box2d-wasm

For typical game physics engines... not that much. Math libraries like Eigen or Blaze use lots of template metaprogramming techniques under the hood that can help when you're doing large batched matrix multiplications (since it can remove temporary allocations at compile-time and can also fuse operations efficiently, as well as applying various SIMD optimizations), but it doesn't really help when you need lots of small operations (with mat3 / mat4 / vec3 / quat / etc.). Typical game physics engines tend to use iterative algorithms for their solvers (Gauss-Seidel, PBD, etc...) instead of batched "matrix"-oriented ones, so you'll get less benefits out of Eigen / Blaze compared to what you typically see in deep learning / scientific computing workloads.

The codebases I've seen in many game physics engines seem to all roll their own math libraries for these stuff, or even just use SIMD (SSE / AVX) intrinsics directly. Examples: PhysX (https://github.com/NVIDIA-Omniverse/PhysX), Box2D (https://github.com/erincatto/box2d), Bullet (https://github.com/bulletphysics/bullet3)...

Box2D: 2D engine used in Unity and also earlier versions of Godot. Open source.

Box2D GitHub repo: erincatto/box2d

Why is 600 lines too long? How are you able to make that judgment call without first knowing what the algorithm is even doing? People setting arbitrary limits like this is what leads to convoluted spaghetti, instead of just taking things on a case by case basis. Here’s a function from the Box2D code running a particularly complex algorithm for solving contact velocities https://github.com/erincatto/box2d/blob/411acc32eb6d4f2e96fc... .

It’s 310 lines long. It reads very well, and it looks very maintainable. It has very clear comments explaining the reasoning behind the harder parts of the code. Would you reject this code because it’s pretty long? I wouldn’t.

There is no such thing as too long or too short. There’s overengineered and there’s underengineered and there’s a sweet spot in the middle that has the perfect amount of engineering with the least amount of complexity (preferably no additional complexity than the original problem warranted). Sometimes, the problem at hand is inherently a large algorithm and requires many lines of code. Don’t split it up! It just makes it harder for future maintainers who now have to figure out if the additional functions are actually being used elsewhere or if they’re just there to make the code “pretty”.

There is always the approach of looking at how an existing engine is implemented, such as box2d: https://github.com/erincatto/box2d

TIL Box2D must not be serious code because it doesn't use copious amounts of explicit temporaries[0].

And just for the record, I'm very glad Erin Catto decided to use operator overloading in his code. It made it much easier for me to read and understand what the code was doing as opposed to it being overly verbose and noisy.

[0]: https://github.com/erincatto/box2d/blob/main/src/collision/b...

For Physics Box2d can be used as a simple starting point.

I suspect most C++ physics libraries like Box2D (https://github.com/erincatto/box2d) or Bullet3 (https://github.com/bulletphysics/bullet3) could really benefit a lot from SIMD.

for 2D physics have a look at Box2D it's amazing https://box2d.org/

https://github.com/Birch-san/box2d-wasm.) Godot uses box2d, too, so that would be convenient, if I switch to godot, but only if it is worth the performance improvement, which it currently does not seem to be. Maybe next year.

Following the article, you build a simple 2D physic simulation (only for balls). Did by chance anyone expand on that to include boxes, or know of a different approach to build a physic engine in WebGPU?

I experiemented a bit with it and imolemented raycasting, but it is really not trivial getting the data in and out. (Limiting it to boxes and circles would satisfy my use case and seems doable, but getting polygons would be very hard, as then you have a dynamic size of their edges to account for and that gives me headache)

3D physic engine on the GPU would be the obvious dream goal to get maximum performance, but that is really not an easy thing to do.

Right now I am using a Box2D for wasm and it has good performance, but it could be better.

https://github.com/Birch-san/box2d-wasm

The main problem with all this is the overhead of getting data into the gpu and back. Once it is on the gpu it is amazingly fast. But the back and forth can really make your framerates drop - so to make it worth it, most of the simulation data has to remain on the gpu and you only put small chanks of data that have changed in and out. And ideally render it all on the gpu in the next step.

(The performance bottleneck of this simulation is exactly that, it gets simulated on the gpu, then retrieved and drawn with the normal canvasAPI which is slow)

box2dwasm - an old, still maintained C++ library compiled to WASM. The documentation is lacking and developer experience seems poor.

network inspector says 2.1MB. but that's dominated by a 1.3MB image.

the main assets of the library are:

- Box2D.simd.js (422kB)

- Box2D.simd.wasm (266 kB)

a minimal demo that uses the library can be created in just a few kB:

https://github.com/Birch-san/box2d-wasm/tree/master/demo/mod...

A couple weeks ago I ported liquidfun to TypeScript + WebAssembly: https://github.com/Birch-san/box2d-wasm/releases/tag/v4.0.0-liquidfun.0