wgpu-lab is a library designed for rapid prototyping of native WebGPU applications in C++. Its main goal is to provide convenient wrappers and intuitive tools for working with WebGPU Dawn, minimizing boilerplate code while remaining flexible and customizable.

I’m developing this library in my free time as I learn the fundamentals of WebGPU. My hope is that it will serve the open source community as a useful resource for learning and as a foundation for building creative projects.

Please note that wgpu-lab is in an early, heavily experimental stage, and the API is likely to undergo significant changes.

Contributions are welcome!

Simple Usage Sample

#include <lab>

struct MyVertexFormat {
  float pos[2];
  float color[3];
};

int main() {
  lab::Webgpu webgpu("My WebGPU Context");
  lab::Shader shader("My Shader", "shaders/draw_colored.wgsl");

  lab::Pipeline pipeline(shader, webgpu); // the rendering pipeline

  // colored triangle data
  std::vector<MyVertexFormat> vertex_data = {
      //         X      Y                R     G     B
      {.pos = {-0.5f, -0.5f}, .color = {0.8f, 0.2f, 0.2f}},
      {.pos = {+0.5f, -0.5f}, .color = {0.8f, 0.8f, 0.2f}},
      {.pos = {+0.0f, +0.5f}, .color = {0.2f, 0.8f, 0.4f}},
  };

  // vertex buffer (sends copy of data to GPU memory)
  lab::Buffer vertex_buffer("My Vertex Buffer", vertex_data, webgpu);

  // pipeline needs to know about buffers and their memory layouts (vertex attributes)
  pipeline.add_vertex_buffer(vertex_buffer);
  pipeline.add_vertex_attrib(wgpu::VertexFormat::Float32x2, 0); // position
  pipeline.add_vertex_attrib(wgpu::VertexFormat::Float32x3, 1); // color
  pipeline.finalize();                                          // make ready for rendering

  lab::Window window("Hello Triangle", 640, 400);

  lab::Surface surface(window, webgpu); // surface to render onto

  // main application loop
  while (lab::tick()) {
    pipeline.render_frame(surface, 3, 1); // 3 vertices, 1 instance
  }
}

Getting Started

Windows

Setup:

1. Install Visual Studio for MSVC compiler and CMake, or a C++ compiler and build tools of your choice (configure it yourself and feel free to share your setup by creating an issue or a pull request)
2. Install VS Code (optional - this project is configured to work well within VS Code)
   open VS Code and install recommended extensions (a pop-up should appear)
   look into the extensions tab to see if C/C++, CMake and CMake Tools are installed
3. Install Python which is required to download dependencies in wgpu-lab and dawn

Build:

1. Clone this repository:

   git clone https://github.com/bv7dev/wgpu-lab.git
   

   or alternatively, download a release build
2. Open the cloned directory or the unzipped release in VS Code (File -> Open Folder...)
3. Hit the ⚙ Build button in Code's bottom toolbar (provided by CMake Tools extension) or use CMake manually to configure and build

The first build takes a long time for downloading, generating and building dawn.

Linux (coming soon)

Mac (help wanted)

Run sample executables:

For VS Code users, there's a shared .vscode/launch.json configuration file. This setup allows you to build and run any .cpp source file that's located in the samples/ directory, simply by opening it in the editor and pressing F5. This runs the code in debug mode (set breakpoints and step through the code to learn how it works).

To get started, you can add your own .cpp file, tinker around and step through the code. Use CMake Tools to reconfigure the project after adding new files.

Dependencies

The library currently only depends on WebGPU Dawn and uses GLFW for windowing, which already comes included with dawn. wgpu-lab also makes heavy use of the C++ STL (see src/extra/lab_public.h). However, to build all of the sample executables, the libraries GLM and tinygltf are also included.

Roadmap

• address build system issues
• re-design render pipeline (too chaotic at the moment)
• replace render_frame() function by smaller, composable mechanisms
• add compute pipeline support
• add emscripten support for WebAssembly
• unify and finalize lab API
• write documentation and tests
• release stable 1.0 version