LiquidFun
box2d-wasm
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LiquidFun | box2d-wasm | |
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12 | 7 | |
4,632 | 243 | |
0.5% | - | |
0.0 | 0.0 | |
11 months ago | almost 2 years ago | |
C++ | TypeScript | |
- | - |
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LiquidFun
- Most Popular C[++] Open-Source Physics Engines
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Show HN: WASM and WebGL Fluid Simulation
Author here. This demo showcases liquidfun-wasm[0], my effort to revive liquidfun[1] (a fork which adds fluid simulation and soft-body physics to Box2D[2]).
to make liquidfun-wasm, I repurposed my existing box2d-wasm[3] and pointed it at a different release of Box2D — a commit obtained by rebasing liquidfun over 7 years of upstream Box2D changes[4]. the end result is that liquidfun is now distributed in WebAssembly and with TypeScript typings for the first time. The TypeScript typings are generated from WebIDL bindings via my webidl-to-ts[5] compiler.
this demo in particular aims to bring to the Web the shaders from the liquidfun EyeCandy demo[6], and show how fast JS can run if you avoid incurring the garbage collector (the main loop tries not to allocate objects). the demo repurposes gravity and drag calculations that I'd used previously in my Lunar Survey experiment[7] (a Mario Galaxy homage).
[0] https://github.com/Birch-san/box2d-wasm/releases/tag/liquidf...
[1] http://google.github.io/liquidfun/
[2] https://github.com/erincatto/box2d
[3] https://github.com/Birch-san/box2d-wasm
[4] https://github.com/Birch-san/box2d-wasm/releases/tag/v4.0.0-...
[5] https://github.com/Birch-san/box2d-wasm/tree/master/webidl-t...
[6] https://github.com/google/liquidfun/blob/master/liquidfun/Bo...
Liquidfun [0] diverged from Box2D at v2.3.0, circa November 2013.
liquidfun-wasm [1] is my effort to rebase the liquidfun contributions onto latest Box2D, v2.4.1 (October 2020), and to distribute it in WebAssembly with TypeScript typings.
this work is detailed in liquidfun-wasm's first release notes. [2]
I've also enabled WASM SIMD acceleration (via LLVM's autovectorizer) on supported devices. Haven't yet measured what performance difference this makes.
yeah, I've played around with a few approaches for running the timestep and for some reason I don't feel like I get the same results as liquidfun.js.
their loop [0] is pretty simple; it's scheduled by `requestAnimationFrame`, advances time by 1/60th of a second, and runs their default of 3 particle iterations. it completes the physics simulation within 3.9–5.5ms, which is easily in time for the 16ms deadline. the rendering is WebGL, which I assume fits easily into that 16ms budget too.
my loop [1] is more complicated; I don't hardcode the timestep to 1/60 seconds, because requestAnimationFrame may be scheduled less frequently than that. so instead I advance time by the time elasped since I was last scheduled. hm, I think there's a mistake there — `lastMs = nowMs` is probably on the wrong side of the physics calculation.
there's an additional technique I use: I put a `Math.min()` over the simulation interval, so that I don't attempt to simulate more than 20ms (this can happen if you get scheduled infrequently due to hot CPU or backgrounding the app) — simulating too much time will make us fail our frame deadline anyway.
furthermore, if we are calculating more than 1/60th of a second, I employ more particle iterations (i.e. 3 particle iterations for every 1/60th of a second that passes). this gave me good results, but turns out it is based on incorrect assumptions (iterations are unrelated to timestep)[3]. moreover, I may be making mistakes in my decision of whether to round this fraction up/down.
if too few particle iterations for a timestep: the particles will bounce. if too many: the particles will look too incompressible[4]. I think that's the "solid-like" structure you're describing.
the main reason I complicated this is because the last one I did[5] made me feel motion-sick. I think if "every 1/60th, or 1/30th, or 1/20th of a second: you simulate a 1/60th of a second of time": the result (if you're not scheduled consistently) is that the world speed keeps changing. I think liquidfun.js's approach should be vulnerable to this, but for some reason it looks fine to me. maybe they get scheduled more consistently than me (even though by my measurements, my physics runs slightly faster, so should be able to achieve similar results).
I think I need to remind myself of what happens if I program the timestep in the simple way that liquidfun.js did. will try that out at some point.
[0] https://github.com/google/liquidfun/blob/master/liquidfun/Bo...
[1] https://github.com/Birch-san/liquidfun-play-2/blob/master/sr...
[2] https://github.com/Birch-san/liquidfun-play-2/blob/master/sr...
[3] http://google.github.io/liquidfun/Programmers-Guide/html/md_...
[4] http://google.github.io/liquidfun/Programmers-Guide/html/md_...
yes, I compiled with -msimd128 to enable LLVM's auto-vectorization. I distribute both SIMD and non-SIMD, and the entrypoint picks whichever distribution your browser supports. for box2d-wasm, SIMD acceleration resulted in a 0.6–0.9% performance boost [0] when simulating a pyramid of boxes.
liquidfun-wasm is a fork with additional algorithms for performantly simulating particles. I have not yet built a benchmark to measure the particle code, but do intend to. I am optimistic that liquidfun's particle code could auto-vectorize better than the general Box2D code.
the Google engineers considered how to take advantage of SIMD, to the extent that they even ship a NEON SIMD algorithm[1]. I don't believe my compiler config will use that NEON algorithm (and will instead fallback to the general algorithm [2]). that's probably not a missed opportunity; many NEON features are not supported[3]. but since the engineers were thinking about SIMD, hopefully the non-NEON algorithm will try to make good use of the CPU and memory layout too, and auto-vectorize well.
[0] https://github.com/Birch-san/box2d.ts/pull/1
[1] https://github.com/google/liquidfun/blob/master/liquidfun/Bo...
[2] https://github.com/google/liquidfun/blob/master/liquidfun/Bo...
[3] https://emscripten.org/docs/porting/simd.html#compiling-simd...
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[AskJS] How could I implement realistic fluids simulations (SPH?) in my video game?
It should be possible to produce simulations like the ones they produced in JS: http://google.github.io/liquidfun/
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Hello!
He was involved in an open-source project titled LiquidFun, which was released late in 2013 and unfortunately only went through 3 versions, ending developmentin mid 2014. https://github.com/google/liquidfun/releases
box2d-wasm
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Article reply “Godot is not the new Unity” from Juan Linietsky (BDFL of Godot)
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.
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WebGPU – All of the cores, none of the canvas
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)
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Running JS physics in a webworker - part 1 - proof of concept
box2dwasm - an old, still maintained C++ library compiled to WASM. The documentation is lacking and developer experience seems poor.
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Show HN: WASM and WebGL Fluid Simulation
Author here. This demo showcases liquidfun-wasm[0], my effort to revive liquidfun[1] (a fork which adds fluid simulation and soft-body physics to Box2D[2]).
to make liquidfun-wasm, I repurposed my existing box2d-wasm[3] and pointed it at a different release of Box2D — a commit obtained by rebasing liquidfun over 7 years of upstream Box2D changes[4]. the end result is that liquidfun is now distributed in WebAssembly and with TypeScript typings for the first time. The TypeScript typings are generated from WebIDL bindings via my webidl-to-ts[5] compiler.
this demo in particular aims to bring to the Web the shaders from the liquidfun EyeCandy demo[6], and show how fast JS can run if you avoid incurring the garbage collector (the main loop tries not to allocate objects). the demo repurposes gravity and drag calculations that I'd used previously in my Lunar Survey experiment[7] (a Mario Galaxy homage).
[0] https://github.com/Birch-san/box2d-wasm/releases/tag/liquidf...
[1] http://google.github.io/liquidfun/
[2] https://github.com/erincatto/box2d
[3] https://github.com/Birch-san/box2d-wasm
[4] https://github.com/Birch-san/box2d-wasm/releases/tag/v4.0.0-...
[5] https://github.com/Birch-san/box2d-wasm/tree/master/webidl-t...
[6] https://github.com/google/liquidfun/blob/master/liquidfun/Bo...
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...
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[AskJS] How could I implement realistic fluids simulations (SPH?) in my video game?
A couple weeks ago I ported liquidfun to TypeScript + WebAssembly: https://github.com/Birch-san/box2d-wasm/releases/tag/v4.0.0-liquidfun.0
What are some alternatives?
rapier - 2D and 3D physics engines focused on performance.
PixiJS - The HTML5 Creation Engine: Create beautiful digital content with the fastest, most flexible 2D WebGL renderer.
Box2D - Box2D is a 2D physics engine for games
box2d.ts - Full blown Box2D Ecosystem for the web, written in TypeScript
libGDX - Desktop/Android/HTML5/iOS Java game development framework
Chipmunk - A fast and lightweight 2D game physics library.
AndEngine - Free Android 2D OpenGL Game Engine
Cocos2d - Cocos2d-x is a suite of open-source, cross-platform, game-development tools utilized by millions of developers across the globe. Its core has evolved to serve as the foundation for Cocos Creator 1.x & 2.x.
Bullet - Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
jbox2d - a 2d Java physics engine, native java port of the C++ physics engines Box2D and LiquidFun
LGame - A cross-platform Java game Engine (Framework) , support JavaFX / Android / IOS / HTML5 / Linux / MAC / Windows
PhysX - NVIDIA PhysX SDK