simple-gpu
Example
simple-webgpu
simplifies WebGPU programming by removing as much shared state as it can get away with. To do this, it replaces the WebGPU API with two fundamental abstractions, resources and commands:
- A resource is a handle to a GPU resident object, like a texture, FBO or buffer.
- A command is a complete representation of the WebGPU state required to perform some draw call.
To define a command you specify a mixture of static and dynamic data for the object. Once this is done, simple-webgpu
takes this description and then compiles it into optimized JavaScript code. For example, here is a simple simple-webgpu
program to draw a triangle:
// importing the webgpu module creates a full screen canvas and
// WebGPU context, and then uses this context to initialize a new webgpu instance
const webgpu = require('simple-webgpu')
// Calling simplewebgpu.init() creates a new partially evaluated draw command
const drawTriangle = webgpu.init({
// Shaders in simplewebgpu. are just strings. You can use glslify or whatever you want
// to define them. No need to manually create shader objects.
frag: `
precision mediump float;
uniform vec4 color;
void main() {
gl_FragColor = color;
}`,
vert: `
precision mediump float;
attribute vec2 position;
void main() {
gl_Position = vec4(position, 0, 1);
}`,
// Here we define the vertex attributes for the above shader
attributes: {
// simplewebgpu.buffer creates a new array buffer object
position: webgpu.buffer([
[-2, -2], // no need to flatten nested arrays, simpleWebgpu automatically
[4, -2], // unrolls them into a typedarray (default Float32)
[4, 4]
])
// simpleWebgpu automatically infers sane defaults for the vertex attribute pointers
},
uniforms: {
// This defines the color of the triangle to be a dynamic variable
color: webgpu.prop('color')
},
// This tells simpleWebgpu the number of vertices to draw in this command
count: 3
})
// webgpu.frame() wraps requestAnimationFrame and also handles viewport changes
webgpu.frame(({time}) => {
// clear contents of the drawing buffer
webgpu.clear({
color: [0, 0, 0, 0],
depth: 1
})
// draw a triangle using the command defined above
drawTriangle({
color: [
Math.cos(time * 0.001),
Math.sin(time * 0.0008),
Math.cos(time * 0.003),
1
]
})
})
See this example live
More examples
Check out the gallery. The source code of all the gallery examples can be found here.
Setup
simple-webgpu
has no dependencies, so setting it up is pretty easy. There are 3 basic ways to do this:
Live editing
just use observablehq.com and
require('simple-webgpu')
npm
The easiest way to use simple-webgpu
in a project is via npm. Once you have node set up, you can install and use simple-webgpu
in your project using the following command:
npm i -S simple-webgpu
For more info on how to use npm, check out the official docs.
If you are using npm, you may also want to try vite
which is a live development server.
Run time error checking and browserify
By default if you compile simple-webgpu
with vite
then all error messages and run time checks are removed. This is done to reduce the size of the final bundle. If you are developing an application, you should run browserify using the --debug
flag in order to enable error messages. This will also generate source maps which make reading the source code of your application easier.
Standalone script tag
You can also use simple-webgpu
as a standalone script if you are really stubborn. The most recent versions can be found in the dist/
folder and is also available from npm cdn in both minified and unminified versions.
- Unminified: https://npmcdn.com/regl/dist/regl.js
- Minified: https://npmcdn.com/regl/dist/regl.min.js
There are some difference when using simple-webgpu
in standalone. Because script tags don't assume any sort of module system, the standalone scripts inject a global constructor function which is equivalent to the module.exports
of simple-webgpu
:
For vanilla HTML in modern browsers, import D3 from jsDelivr:
<!DOCTYPE html>
<html>
<head>
<meta content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=0" name="viewport" />
<meta charset=utf-8>
</head>
<body>
</body>
<script language="javascript" type="module">
import webgpu from "https://cdn.jsdelivr.net/npm/simple-gpu/+esm";
let webgpu = webgpu.init()
webgpu.frame(function () {
webgpu.clear({
color: [0, 0, 0, 1]
})
})
</script>
</html>
simple-webgpu
Why simple-webgpu
just removes shared state from WebGPU. You can do anything you could in regular WebGPU with little overhead and way less debugging. regl
emphasizes the following values:
- Simplicity The interface is concise and emphasizes separation of concerns. Removing shared state helps localize the effects and interactions of code, making it easier to reason about.
-
Correctness
simple-webgpu
has more than 30,000 unit tests and above 95% code coverage. In development mode,regl
performs strong validation and sanity checks on all input data to help you catch errors faster. -
Performance
simple-webgpu
uses partial evaluation to remove almost all overhead. -
Minimalism
simple-webgpu
just wraps WebGPU. It is not a game engine and doesn't have opinions about scene graphs or vector math libraries. Any feature in WebGPU is accessible, including advanced extensions like TODO -
Stability
simple-webgpu
takes interface compatibility and semantic versioning seriously, making it well suited for long lived applications that must be supported for months or years down the road. It also has no dependencies limiting exposure to risky or unplanned updates.
Benchmarks
In order to prevent performance regressions, simple-webgpu
is continuously
benchmarked. You can run benchmarks locally using npm run bench
or
check them out
online. The
results for the last few days can be found
here.
TODO
These measurements were taken using our custom scripts bench-history
and
bench-graph
. You can read more about them in the development guide.
Projects using simple-webgpu
The following is an incomplete list of projects using regl:
If you have a project using regl that isn't on this list that you would like to see added, please send us a pull request!
Help Wanted
simple-webgpu is still under active developement, and anyone willing to contribute is very much welcome to do so. Right now, what we need the most is for people to write examples and demos with the framework. This will allow us to find bugs and deficiencies in the API. We have a list of examples we would like to be implemented here, but you are of course welcome to come up with your own examples. To add an example to our gallery of examples, please send us a pull request!
API docs
simple-webgpu
has extensive API documentation. You can browse the docs online here.
Development
The latest changes in simple-webgpu
can be found in the CHANGELOG.
For info on how to build and test headless, see the contributing guide here
License
All code (c) 2022 BSD License
Asset licenses
TODO
Many examples use creative commons or public domain artwork for illustrative purposes. These assets are not included in any of the redistributable packages of regl.
- Peppers test image for cube comparison is public domain
- Test video (doggie-chromakey.ogv) by L0ckergn0me, used under creative commons license
- Cube maps (posx.jpeg, negx.jpeg, posy.jpeg, negy.jpeg, posz.jpeg, negz.jpeg) by Humus, used under creative commons 3 license
- Environment map of Oregon (ogd-oregon-360.jpg) due to Max Ogden (@maxogd on GitHub)
- DDS test images (alpine_cliff_a, alpine_cliff_a_norm, alpine_cliff_a_spec) taken from the CC0 license 0-AD texture pack by Wildfire games
- Tile set for tile mapping demo (tiles.png) from CC0 licensed cobblestone paths pack
- Audio track for
audio.js
example is "Bamboo Cactus" by 8bitpeoples. CC BY-ND-NC 1.0 license - Matcap (spheretexture.jpg) by Ben Simonds. CC 3 license.
- Normal map (normaltexture.jpg) by rubberduck. CC0 license.
Regl Homage
Simple-webgpu is an intentional homage of my favorite WebGL module, click here to view the original, and also d3. My goal with this module was to keep the essence of regl and make it possible to translate the demos with minimal transpilation of just shader code, while keeping the data-fallthrough elements of d3.
Platinum Sp onsors
TODO
- [ ] use vite locally and rollup to build bundle
- [ ] import module in jupyter notebook (double users, plotly)
- [ ] autocreate bindgroups
- [ ] implement regl api
- [ ] implement reactive constructors in javascript (maybe, vue)
- [ ] use d3 in demos to set pattern for uniforms for now
- [ ] https://bost.ocks.org/mike/join - uniforms/attributes
Development
when developing locally, use npm run dev - change the module import from
import webgpu from "https://cdn.jsdelivr.net/npm/simple-gpu/+esm";
to import simpleWebGpu from
import webgpu from "../lib/main";
TODO
- [] glass of water
- [] PBR demo
- [] matrix multiply demo https://milhidaka.github.io/webgpu-blas/ https://gpu.rocks/#/
- [] write docs on auto-create bindgroups
- [] always render to a renderTarget not canvas because more composable
- [ ] mixins
- [] https://github.com/mattatz/THREE.Watercolor
- [] sentiment analysis
developing locally
npm run dev
https://www.youtube.com/watch?v=Jl06sOvMnvU
//https://www.khronos.org/assets/uploads/developers/presentations/WebGPU_Best_Practices_Google.pdf