# Learning Resources

## WebGPU

- [WebGPU Samples](https://webgpu.github.io/webgpu-samples/) - Sample code (some of these samples were adapted to luma.gl)
- [Raw WebGPU](https://alain.xyz/blog/raw-webgpu) - A WebGPU tutorial
- [WebGPU Fundamentals](https://webgpufundamentals.org/) - Walkthroughs
- [WebGPU — All of the cores, none of the canvas](https://surma.dev/things/webgpu/) - About WebGPU compute
- [WebGPU specification](https://gpuweb.github.io/gpuweb/)
- [WGSL specification](https://gpuweb.github.io/gpuweb/wgsl/) 
- [Efficiently rendering glTF models](https://toji.dev/webgpu-gltf-case-study/) This superb case study by Brandon Jones contains a substantial amount of information about how WebGPU differs from WebGL.

## WebGL

 - [WebGL 2 Fundamentals](https://webgl2fundamentals.org/) - Recommended if you are unfamiliar with how to draw with WebGL.
 - [WebGL 2 Specification](https://registry.khronos.org/webgl/specs/latest/2.0/)
 - [OpenGL ES 3.0 Specification](https://registry.khronos.org/OpenGL/specs/es/3.0/es_spec_3.0.pdf)
 - [GLSL ES 3.0 Specification](https://registry.khronos.org/OpenGL/specs/es/3.0/GLSL_ES_Specification_3.00.pdf
  
## glTF

- [glTF 2.0 Specification](https://registry.khronos.org/glTF/specs/2.0/glTF-2.0.html)
- [Efficiently rendering glTF models](https://toji.dev/webgpu-gltf-case-study/) Again, this case study by Brandon Jones contains a substantial amount of information about how glTF is implemented.