voxelis 25.4.0

Sparse Voxel Octree DAG engine for building worlds, shaping matter, and mastering 3D space — powered by pure Rust.
Documentation

"Need voxels? Reach for Voxelis." Powered by VoxTree — a deliciously crafted SVO DAG with batching. Drop it into your Rust, C++, Godot, or Bevy project and start carving worlds down to centimetre-level detail — while your memory bill stays shockingly low.

🚀 Why Voxelis?

  • Tiny voxels (4 cm resolution) without melting your RAM.
  • Shared memory — DAG compression at 99.999% ratio.
  • Batch edits — mutate hundreds of thousands of voxels in a blink.
  • Zero garbage collection — just deterministic reference counting with generations.
  • Built for gamedev — chunk grids, paging hooks, multithread-ready.
  • Fearless Rust — no UB, no data races, only pure, undiluted speed.

This isn't just another voxel crate. It's a foundation for colossal, high-fidelity worlds.

âœĻ Benchmarks: "Speed so fast, it hurts."

Operation 32Âģ Voxels Single Op Batch Op Notes
fill() 32K 9 ns 10.6 ns ⚡ Single leaf collapse
set_uniform() 32K 5.17 ms 23.1 Ξs 🚀 ~224× faster
set_checkerboard() 32K 2.52 ms 116.6 Ξs 🚀 ~22× faster
set_sum() (high-entropy) 32K 5.92 ms 194.1 Ξs 🌊ïļ Complex pattern, ~30× faster
perlin dunes (high-entropy) 32K - ~12 Ξs 🌎 ~1380 chunks/frame (60 FPS)

Full raw results? Check benches-raw.md.

Summary tables? See benches-tables.md.

Full commentary and insights? Dive into benches.md.

🔧 Quick Start

use voxelis::{VoxTree, VoxInterner};
use glam::IVec3;

let mut interner = VoxInterner::<u8>::with_memory_budget(256 * 1024 * 1024);
let mut tree = VoxTree::new(5); // 32Âģ voxels (chunk)

let mut batch = tree.create_batch();
batch.fill(&mut interner, 0); // air
batch.set(&mut interner, IVec3::new(3,0,4), 1); // stone

tree.apply_batch(&mut interner, &batch)?;
assert_eq!(tree.get(&interner, IVec3::new(3,0,4)), Some(1));

Add via Cargo:

cargo add voxelis # Requires Rust 1.86+, optionally use `wide` for SIMD meshing

🔍 Under the Hood

Concept Purpose
VoxTree The SVO-DAG — compressed octree core.
VoxInterner Shared memory for leaves/branches. Hash-consed.
Batch Bottom-up batched editing — mutate at light speed.
VoxOps Trait for per-voxel manipulation — set, get, fill, clear.
BlockId 64-bit magic to encode voxel state compactly.
Mesher SIMD greedy meshing (WIP) — turn voxels into worlds.

More? Crack open The Voxelis Bible (docs/The Voxelis Bible_ From Pixels to Worlds - An In-Depth Guide v2.3.pdf) — 38 pages of dangerously concentrated nerdery.

🌏 Roadmap: Into the Voxelverse

  • Multithreaded interner with Rayon.
  • GreedyMesh v2 (distance-field LOD magic).
  • GPU frustum-culling traversals.
  • OBJ / glTF import/export.
  • True out-of-core paging (MMAP + LRU).

PRs welcome. Bonus points if your patch makes the CI bot 🐈‍🔄 purr.

ðŸšĄ Run Your Own Benches

cargo bench -p voxelis_bench

Hardware: Apple M3 Max, Rust 1.86 stable, -C target-cpu=native, final profile.

Want real numbers? We've got them — benches-tables.md and benches-raw.md await.

👍 Contributing

  1. Fork and branch (feat/my-magnificent-contribution).
  2. cargo test && cargo bench
  3. Open PR, include new benchmark delta.
  4. Bask in voxel-induced glory.

🌐 License

Dual licensed under MIT / Apache-2.0. Pick your poison, build something massive.

⚠ïļ Warning

Voxelis may cause extreme enthusiasm, uncontrollable world-building, and compulsive Rust evangelism. Consult your GPU before operating heavy voxel engines. 😜