Very interesting to watch, though I don't really have a great idea of what's going on most of the time. Performance seems to be fairly poor despite my system being pretty beefy (Ryzen 9 7950x3d). I see the performance monitor and notice that the render loop seems to fairly regularly exceed the latency for 60fps, despite this being a 'simple' task by modern standards. I'd give more helpful feedback as to why, but the minified code makes it hard to say.

Do you plan on monetizing this somehow? If not, open sourcing some, if not all, would be pretty cool, even if it weren't necessarily licensed in a way that others could 'take' it, if that's your concern. Nonetheless, a very cool project.

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PunchyHamster 4 hours ago | parent [-]

it runs slow for me too but also doesn't peak the CPU core

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geminigemino 3 hours ago | parent | next [-]

FPS dips usually line up with big ecological events (population blooms, mass reproduction, lots of giant organisms, pathogen waves). The sim and rendering are decoupled, so you get (hopefully) brief spikes when a lot happens at once, then it settles again as populations crash/thin out. It’s normal behavior, not a runaway bug.

I’ve spent a lot of time optimizing hot paths and getting calculations down, but when the ecology goes a bit wild, you’ll still see temporary spikes. If you want to focus on stats only, you can switch to Simmer mode (no graphs) or turn off the arena, which reduces rendering work quite a bit.

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senfiaj 3 hours ago | parent | prev [-]

I guess some O(n^2) algorithm.

	▲	geminigemino 3 hours ago \| parent [-]
		Yes, some parts are inherently O(n²) (mate finding, crowd density, predator/prey proximity, pathogen spread). Ecology needs pairwise relationships. To keep it sane, I don’t do naive all-vs-all. I use: Zone-based spatial indexing so most checks only run against local neighbors (roughly n/16 instead of n). Temporal caching of indices so they’re not rebuilt every tick. Statistical sampling for crowd density at high population (estimate from a fixed-size sample instead of full scans). So in practice it’s closer to O(n² / k), with k ≈ 16–50 depending on zone layout and population. You still see spikes during blooms, but it’s usually 10–30× faster than naive pairwise checks.