Archetype Asset

Fast, modular asset system for high-performance Rust game engines.

Features

• Backend Agnostic: Generic GpuDevice abstraction (Vulkan ready, Mock provided).
• Runtime Agnostic: Generic AsyncSpawner (Tokio support, Mock provided).
• Spatial Preloading: Background loading based on player position.
• LOD Generation: Automatic mesh simplification using meshopt.
• Concurrency: High-performance caching with DashMap.
• Memory Pooling: Reduced fragmentation for geometry data.

Quick Start

use archetype_asset::cache::AssetCache;
use archetype_asset::gpu::mock::MockGpu;
use archetype_asset::runtime::tokio::TokioSpawner; // requires feature "runtime-tokio"

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // 1. Initialize GPU and Spawner
    let gpu = MockGpu::new(); // Or your real GpuDevice impl
    let spawner = TokioSpawner::new();
    
    // 2. Create Cache (100MB limit)
    let cache = AssetCache::new(gpu, spawner, 100 * 1024 * 1024);

    // 3. Load Asset
    let model = cache.get_or_load_model("assets/my_model.glb").await?;
    
    println!("Loaded model with {} meshes", model.meshes.len());
    Ok(())
}

Architecture

See ARCHITECTURAL_GUIDE.md for a deep dive into the system design, including the caching strategy, memory pooling, and spatial system.

Performance

• Zero-Copy Uploads: Assets move from disk to GPU with minimal overhead.

• Async Pipeline: Loading does not stall the main thread.

• Smart Eviction: LRU-based eviction ensures memory budget compliance.

• Proven Efficiency:

  • 20% faster model loader instantiation.
  • 7% faster cache hit lookups.
  • Zero allocation mesh creation path.

  Benchmarks run on Intel Core i5-11400F, Intel Arc A380, 16GB RAM.