simple-webgpu-compute

...

module for using webgpu for data visualization and more make compute shaders as simple as possible minimalist runtime for using webgpu shaders in nb/static website

 import {init} from "https://cdn.skypack.dev/simple-data-texture/"


let options = {}

let draw = init(options)

let uniformData = {}

draw(uniformData)

 import {init, Texture} from "https://cdn.skypack.dev/simple-data-texture/"


let catTexture = Texture('http://giphy.com/cat_pic.png');
let dogTexture = Texture('http://giphy.com/dog.png');

let draw = init({
  data: {time: 123, texture:catTexture}
})

draw({texture: dogTexture})

cat.subImage({
  width: 200, height: 200,
  data: dogTexture.read({x:5,y:5,w:200,h: 200})
}, 1,1)

//todo make api easier //todo make textures stream and pipe through compute

this library currently just draws a quad and allows custom shaders with minimal boilerplate custom uniforms and textures

• TopLevel Functions init -> returns draw Texture

• Default Options

WidthxHeight

1. passed in explicitly
2. check canvas
3. if neither 1,2 default to 900x500

• References http://vis.stanford.edu/files/2013-imMens-EuroVis.pdf (what is the right name for data-cubes/megatextures/virtual-streaming-textures/etc??) https://observablehq.com/@observablehq/downloading-and-embedding-notebooks

techniques for faster load time (start with lossy to load instantly, fill in with accurate data as user gets closer adjusting level of detail ) png/jpeg https://developers.google.com/protocol-buffers column-based data-stores like arrow/cassandra mega-textures from id-engine-5 (virtual-streaming textures ) immens / nanocubes https://scale.com/resources/download/pandaset https://nanocubes.net/ https://www1.nyc.gov/site/doitt/initiatives/3d-building.page https://explorer.morphocode.com/map