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Rust / GPU / Creative tools

RustingStudio

Engines, intelligence, and graphics.

We explore how Rust and GPU computing can reshape game engines, machine learning, and real-time graphics.

BUILD. MEASURE. CREATE.
01 / 04Game engine
RustingEngine

A Rust game engine with Vulkan rendering, an editor, and hybrid CPU/GPU physics.

02 / 04Deep learning
RustingBrain

A deep-learning library in Rust, from small networks to transformer models.

03 / 04Shader pack
RustingShader

A cinematic Iris shader pack for Minecraft, with a black hole in the End.

04 / 04LLM inference
RustingStrata

A pure-Rust inference engine for Qwen3.5/3.6 MoE models that splits experts between GPU and CPU.

01 / 04
Game engine / Vulkan / Physics

RustingEngine

A GPU-first game engine for physics-heavy scenes. Vulkan rendering, a Blender-style editor, and hybrid physics — you decide what the CPU owns and what the GPU simulates.

2,191FPS
10,000 GPU-simulated cubes
7
CPU joint types, hinge to six-axis
2
Platforms: Linux and Windows
Measured on an RTX 3060.
PBR + shadowsGPU frustum cullingDeterministic scenariosrusting CLI
src/game.rsrust
use rusting_engine::prelude::*;

fn update(scene: &mut GameScene<'_>, time: &FrameTime) {
    scene.object("Planet").rotate_y(0.2 * time.delta_seconds());
}

rusting_game!(update);
02 / 04
Deep learning / CUDA / Metal

RustingBrain

Train anything from an XOR network to a 300M-parameter transformer on one desktop GPU. No Python, no C++ build step — CUDA kernels compile at startup.

300M
Parameter LMs on a single GPU
3
Backends: CPU, CUDA, Metal
16
Tutorial chapters, zero to LM
Matches or beats PyTorch on most RTX 3060 configurations.
Flash attentionMixture of ExpertsLoRA fine-tuningBF16
examples/xor.rsrust
let mut model = Network::builder()
    .input_size(2)
    .dense(8, Activation::Tanh)
    .dense(1, Activation::Sigmoid)
    .loss(Loss::BinaryCrossEntropy)
    .optimizer(Optimizer::adam(0.05))
    .build();
03 / 04
Shader pack / GLSL / Iris

RustingShader

A cinematic shader pack for Minecraft Java Edition. Soft PCSS shadows, deferred water with caustics, volumetric clouds and light — and a gravitationally lensed black hole in the End.

PCSS
Soft shadows, deferred lighting
3
Dimensions, each lit its own way
GL 3
Runs through Iris on OpenGL 3.x
Developed on an RTX 3060.
Volumetric cloudsWater causticsLensed black holeBloom + auto-exposure
installbash
# 1. Install Iris for Minecraft Java Edition
# 2. Download the latest RustingShader release
$ mv RustingShader.zip ~/.minecraft/shaderpacks/
# 3. Video Settings → Shader Packs → RustingShader
04 / 04
LLM inference / CUDA / Qwen

RustingStrata

Run Qwen3.6-35B-A3B on a 12 GB GPU faster than llama.cpp. Experts that do not fit in VRAM run on the CPU alongside the GPU, and their placement adapts to the routing it sees. No C++, no ggml — CUDA kernels compile at run time.

2,093
tok/s prefill at 4K (llama.cpp: 1,017)
101
tok/s decode (llama.cpp: 65.8)
111
tok/s decode with MTP drafts
Qwen3.6-35B-A3B Q2_K_XL (11.7 GiB) on an RTX 3060 12 GB + Ryzen 5 7600X.
Hybrid CPU/GPU MoEAdaptive expert placementMTP speculative decodingOpenAI-compatible server
runbash
$ cargo build --release
$ strata calibrate --model $M
$ strata chat --model $M --gpu
$ strata serve --model $M --gpu --addr 127.0.0.1:8080