React Native WebGPU

React Native implementation of WebGPU using Dawn.
This is currently a technical preview for early adopters.

Installation

Please note that the package name is react-native-wgpu.

npm install react-native-wgpu

Below are some examples from the example app.

github3.mp4

Starting from r168, Three.js runs out of the box with React Native WebGPU. You need to have a slight modification of the metro config to resolve Three.js to the WebGPU build. We also support three-fiber. For model loading, we also need the following polyfill.

threejs.mp4

We also provide prebuilt binaries for visionOS and macOS.

CleanShot.2024-08-26.at.16.24.41.mp4

Usage

Currently we recommend to use the useCanvasEffect to access the WebGPU context.

import React from "react";
import { StyleSheet, View, PixelRatio } from "react-native";
import { Canvas, useCanvasEffect } from "react-native-wgpu";

import { redFragWGSL, triangleVertWGSL } from "./triangle";

export function HelloTriangle() {
  const ref = useCanvasEffect(async () => {
    const adapter = await navigator.gpu.requestAdapter();
    if (!adapter) {
      throw new Error("No adapter");
    }
    const device = await adapter.requestDevice();
    const presentationFormat = navigator.gpu.getPreferredCanvasFormat();

    const context = ref.current!.getContext("webgpu")!;
    const canvas = context.canvas as HTMLCanvasElement;
    canvas.width = canvas.clientWidth * PixelRatio.get();
    canvas.height = canvas.clientHeight * PixelRatio.get();

    if (!context) {
      throw new Error("No context");
    }

    context.configure({
      device,
      format: presentationFormat,
      alphaMode: "opaque",
    });

    const pipeline = device.createRenderPipeline({
      layout: "auto",
      vertex: {
        module: device.createShaderModule({
          code: triangleVertWGSL,
        }),
        entryPoint: "main",
      },
      fragment: {
        module: device.createShaderModule({
          code: redFragWGSL,
        }),
        entryPoint: "main",
        targets: [
          {
            format: presentationFormat,
          },
        ],
      },
      primitive: {
        topology: "triangle-list",
      },
    });

    const commandEncoder = device.createCommandEncoder();

    const textureView = context.getCurrentTexture().createView();

    const renderPassDescriptor: GPURenderPassDescriptor = {
      colorAttachments: [
        {
          view: textureView,
          clearValue: [0, 0, 0, 1],
          loadOp: "clear",
          storeOp: "store",
        },
      ],
    };

    const passEncoder = commandEncoder.beginRenderPass(renderPassDescriptor);
    passEncoder.setPipeline(pipeline);
    passEncoder.draw(3);
    passEncoder.end();

    device.queue.submit([commandEncoder.finish()]);

    context.present();
  });

  return (
    <View style={style.container}>
      <Canvas ref={ref} style={style.webgpu} />
    </View>
  );
}

const style = StyleSheet.create({
  container: {
    flex: 1,
  },
  webgpu: {
    flex: 1,
  },
});

Example App

To run the example app you first need to build Dawn or download the prebuilt binaries.

From there you will be able to run the example app properly.

Similarities and Differences with the Web

The API has been designed to be completely symmetric with the Web.
For instance, you can access the WebGPU context synchronously, as well as the canvas size.
Pixel density and canvas resizing are handled exactly like on the Web as well.

// The default canvas size is not scaled to the device pixel ratio
// When resizing the canvas, the clientWidth and clientHeight are updated automatically
// This behaviour is symmetric to the Web
const ctx = canvas.current.getContext("webgpu")!;
ctx.canvas.width = ctx.canvas.clientWidth * PixelRatio.get();
ctx.canvas.height = ctx.canvas.clientHeight * PixelRatio.get();

Frame Scheduling

In React Native, we want to keep frame presentation as a manual operation as we plan to provide more advanced rendering options that are React Native specific.
This means that when you are ready to present a frame, you need to call present on the context.

// draw
// submit to the queue
device.queue.submit([commandEncoder.finish()]);
// This method is React Native only
context.present();

External Textures

This module provides a createImageBitmap function that you can use in copyExternalImageToTexture.

const url = Image.resolveAssetSource(require("./assets/image.png")).uri;
const response = await fetch(url);
const imageBitmap = await createImageBitmap(await response.blob());

const texture = device.createTexture({
  size: [imageBitmap.width, imageBitmap.height, 1],
  format: "rgba8unorm",
  usage:
    GPUTextureUsage.TEXTURE_BINDING |
    GPUTextureUsage.COPY_DST |
    GPUTextureUsage.RENDER_ATTACHMENT,
});
device.queue.copyExternalImageToTexture(
  { source: imageBitmap },
  { texture },
  [imageBitmap.width, imageBitmap.height],
);

Troubleshooting

iOS

To run the React Native WebGPU project on the iOS simulator, you need to disable the Metal validation API.
In "Edit Scheme," uncheck "Metal Validation."

Android

On an Android simulator, a CPU emulation layer is used which may result in very slow performance.

Library Development

Make sure to check out the submodules:

git submodule update --init

Make sure you have all the tools required for building the Skia libraries (Android Studio, XCode, Ninja, CMake, Android NDK/build tools).

Building Dawn

yarn
cd packages/webgpu
yarn build-dawn

You can also filter the platforms to build, for instance to skip the macOS and visionOS build:

yarn build-dawn --exclude=xros,xrsimulator,macosx

Alternatively if you want to build for a specific platform only, you can use includeOnly.

yarn build-dawn --includeOnly=xros,xrsimulator

Downloading Dawn

There is an alternative way which is to download the prebuilt binaries from GitHub. You need to have the Github CLI installed:

$ yarn
$ cd packages/webgpu
$ yarn download-artifacts

Alternatively you can also download the prebuilt binaries here.

Upgrading

1. git submodule update --remote
2. yarn clean-dawn
3. yarn build-dawn

Codegen

• cd packages/webgpu && yarn codegen

Testing

In the package folder, to run the test against Chrome for reference:

yarn test:ref

To run the e2e test, open the example app on the e2e screen.
By default, it will try to connect to a localhost test server.
If you want to run the test suite on a physical device, you can modify the address here.

yarn test