https://github.com/wildpixelgames/voxelis
Tiny voxels. Huge worlds. Voxelis — a pure Rust voxel engine based on Sparse Voxel Octree DAG.
https://github.com/wildpixelgames/voxelis
3d dag data-structures engine game-development gamedev graphics octree procedural-generation rust simulation sparse-voxel-octree svo voxel voxel-engine
Last synced: about 1 month ago
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Tiny voxels. Huge worlds. Voxelis — a pure Rust voxel engine based on Sparse Voxel Octree DAG.
- Host: GitHub
- URL: https://github.com/wildpixelgames/voxelis
- Owner: WildPixelGames
- License: apache-2.0
- Created: 2025-04-27T23:05:34.000Z (about 1 month ago)
- Default Branch: master
- Last Pushed: 2025-04-28T04:47:29.000Z (about 1 month ago)
- Last Synced: 2025-04-28T16:19:53.296Z (about 1 month ago)
- Topics: 3d, dag, data-structures, engine, game-development, gamedev, graphics, octree, procedural-generation, rust, simulation, sparse-voxel-octree, svo, voxel, voxel-engine
- Language: Rust
- Homepage: https://github.com/WildPixelGames/voxelis
- Size: 3.33 MB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE-APACHE
Awesome Lists containing this project
README
Tiny voxels. Huge worlds. Zero hassle.
> **"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.
---
## ✨ Benchmarks: "Speed so fast, it hurts."
| Operation | 32³ Voxels | Single Op | Batch Op | Notes |
|----------------------------------|-------------|-------------|-------------|-------|
| **fill()** | 32K | **9 ns** | **10.6 ns** | ⚡ Single leaf collapse |
| **set_uniform()** | 32K | **5.17 ms** | **23.1 μs** | 🚀 ~224× faster |
| **set_checkerboard()** | 32K | **2.52 ms** | **116.6 μs** | 🚀 ~22× faster |
| **set_sum() (high-entropy)** | 32K | **5.92 ms** | **194.1 μs** | 🌪️ Complex pattern, ~30× faster |
| **perlin dunes (high-entropy)** | 32K | - | **~12 μs** | 🌎 ~1380 chunks/frame (60 FPS) |
> Full raw results? Check [benches-raw.md](https://github.com/WildPixelGames/voxelis/blob/master/docs/benches-raw.md).
>
> Summary tables? See [benches-tables.md](https://github.com/WildPixelGames/voxelis/blob/master/docs/benches-tables.md).
>
> Full commentary and insights? Dive into [benches.md](https://github.com/WildPixelGames/voxelis/blob/master/docs/benches.md).
---
## 🔧 Quick Start
```rust
use glam::IVec3;
use voxelis::{
MaxDepth, VoxInterner,
spatial::{VoxOpsBatch, VoxOpsRead, VoxOpsWrite, VoxTree},
};
fn main() {
let mut interner = VoxInterner::::with_memory_budget(256 * 1024 * 1024);
let mut tree = VoxTree::new(MaxDepth::new(5)); // 32³ voxels (chunk)
let mut batch = tree.create_batch();
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:
```bash
cargo add voxelis [email protected] # 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](https://github.com/WildPixelGames/voxelis/blob/master/docs/The%20Voxelis%20Bible_%20From%20Pixels%20to%20Worlds%20-%20An%20In-Depth%20Guide%20v2.3.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.
---
## 🚡 Run Your Own Benches
```bash
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](https://github.com/WildPixelGames/voxelis/blob/master/docs/benches-tables.md) and [benches-raw.md](https://github.com/WildPixelGames/voxelis/blob/master/docs/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.
---
## ⚠️ Warning
Voxelis may cause extreme enthusiasm, uncontrollable world-building, and compulsive Rust evangelism. Consult your GPU before operating heavy voxel engines. 😜