React Native implementation of WebGPU using Dawn.
This is currently a technical preview for early adopters.
React Native WebGPU requires React Native 0.81 or newer and doesn't run on legacy architecture.
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 react-three-fiber; to make it work, patch node_modules/@react-three/fiber/package.json (for instance via patch-package) so that it resolves to the WebGPU entry point instead of the React Native bundle:
diff --git a/node_modules/@react-three/fiber/package.json b/node_modules/@react-three/fiber/package.json
@@
- "react-native": "native/dist/react-three-fiber-native.cjs.js",
+ "react-native": "dist/react-three-fiber.cjs.js",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 is identical to Web.
import React from "react";
import { StyleSheet, View, PixelRatio } from "react-native";
import { Canvas, CanvasRef } from "react-native-wgpu";
import { redFragWGSL, triangleVertWGSL } from "./triangle";
export function HelloTriangle() {
const ref = useRef<CanvasRef>(null);
useEffect(() => {
const helloTriangle = 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();
};
helloTriangle();
}, [ref]);
return (
<View style={style.container}>
<Canvas ref={ref} style={style.webgpu} />
</View>
);
}
const style = StyleSheet.create({
container: {
flex: 1,
},
webgpu: {
flex: 1,
},
});To run the example app you first need to install Dawn.
From there you will be able to run the example app properly.
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();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();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],
);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". Learn more here.
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).
There is an alternative way which is to install the prebuilt binaries from GitHub.
$ yarn
$ cd packages/webgpu
$ yarn install-dawnAlternatively, you can build Dawn locally.
yarn
cd packages/webgpu
yarn build-dawngit submodule update --remoteyarn clean-dawnyarn build-dawn
cd packages/webgpu && yarn codegen
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