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[webassembly]Compare pure ES/wasm/asm.js with Turing Pattern example
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function asm(global, env, heap) { | |
"use asm"; | |
var imul = global.Math.imul; | |
var buf = new global.Float64Array(heap); | |
function get(offs, w, x, y) { | |
offs = offs | 0; | |
w = w | 0; | |
x = x | 0; | |
y = y | 0; | |
var index = 0; | |
index = (imul((y + w >>> 0) % (w >>> 0) | 0, w) | 0) + | |
((x + w >>> 0) % (w >>> 0) | 0) | 0; | |
return +buf[(offs + (index << 3)) >> 3]; | |
} | |
function conv(coffs, cr, soffs, w, h, doffs) { | |
coffs = coffs | 0; | |
cr = cr | 0; | |
soffs = soffs | 0; | |
w = w | 0; | |
h = h | 0; | |
doffs = doffs | 0; | |
var x = 0, y = 0, cx = 0, cy = 0, cw = 0; | |
var s = 0.0; | |
cw = (imul(cr, 2) | 0) + 1 | 0; | |
for (y = 0; (y | 0) < (h | 0); y = y + 1 | 0) { | |
for (x = 0; (x | 0) < (w | 0); x = x + 1 | 0) { | |
s = 0.0; | |
for (cy = -cr | 0; (cy | 0) <= (cr | 0); cy = cy + 1 | 0) { | |
for (cx = -cr | 0; (cx | 0) <= (cr | 0); cx = cx + 1 | 0) { | |
s = s + +get(coffs, cw, cx + cr | 0, cy + cr | 0) * | |
+get(soffs, w, x + cx | 0, y + cy | 0); | |
} | |
} | |
buf[(doffs + (((imul(y, w) | 0) + x) << 3)) >> 3] = +s; | |
} | |
} | |
} | |
return {conv: conv}; | |
} |
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(module | |
(export "heap" (memory $0)) | |
(export "conv" (func $conv)) | |
(memory $0 1 256) | |
(func $get (param $offs i32) (param $w i32) (param $x i32) (param $y i32) (result f64) | |
(local $index i32) | |
(set_local $index | |
(i32.add | |
(i32.mul | |
(i32.rem_u | |
(i32.add | |
(get_local $y) | |
(get_local $w) | |
) | |
(get_local $w) | |
) | |
(get_local $w) | |
) | |
(i32.rem_u | |
(i32.add | |
(get_local $x) | |
(get_local $w) | |
) | |
(get_local $w) | |
) | |
) | |
) | |
(return | |
(f64.load | |
(i32.add | |
(get_local $offs) | |
(i32.shl | |
(get_local $index) | |
(i32.const 3) | |
) | |
) | |
) | |
) | |
) | |
(func $conv (param $coffs i32) (param $cr i32) (param $soffs i32) (param $w i32) (param $h i32) (param $doffs i32) | |
(local $x i32) | |
(local $y i32) | |
(local $cx i32) | |
(local $cy i32) | |
(local $cw i32) | |
(local $s f64) | |
(set_local $cw | |
(i32.add | |
(i32.mul | |
(get_local $cr) | |
(i32.const 2) | |
) | |
(i32.const 1) | |
) | |
) | |
(block | |
(set_local $y | |
(i32.const 0) | |
) | |
(loop $for-in | |
(block $for-out | |
(if | |
(i32.eqz | |
(i32.lt_s | |
(get_local $y) | |
(get_local $h) | |
) | |
) | |
(br $for-out) | |
) | |
(block | |
(set_local $x | |
(i32.const 0) | |
) | |
(loop $for-in1 | |
(block $for-out0 | |
(if | |
(i32.eqz | |
(i32.lt_s | |
(get_local $x) | |
(get_local $w) | |
) | |
) | |
(br $for-out0) | |
) | |
(block | |
(set_local $s | |
(f64.const 0) | |
) | |
(block | |
(set_local $cy | |
(i32.sub | |
(i32.const 0) | |
(get_local $cr) | |
) | |
) | |
(loop $for-in3 | |
(block $for-out2 | |
(if | |
(i32.eqz | |
(i32.le_s | |
(get_local $cy) | |
(get_local $cr) | |
) | |
) | |
(br $for-out2) | |
) | |
(block | |
(set_local $cx | |
(i32.sub | |
(i32.const 0) | |
(get_local $cr) | |
) | |
) | |
(loop $for-in5 | |
(block $for-out4 | |
(if | |
(i32.eqz | |
(i32.le_s | |
(get_local $cx) | |
(get_local $cr) | |
) | |
) | |
(br $for-out4) | |
) | |
(set_local $s | |
(f64.add | |
(get_local $s) | |
(f64.mul | |
(call $get | |
(get_local $coffs) | |
(get_local $cw) | |
(i32.add | |
(get_local $cx) | |
(get_local $cr) | |
) | |
(i32.add | |
(get_local $cy) | |
(get_local $cr) | |
) | |
) | |
(call $get | |
(get_local $soffs) | |
(get_local $w) | |
(i32.add | |
(get_local $x) | |
(get_local $cx) | |
) | |
(i32.add | |
(get_local $y) | |
(get_local $cy) | |
) | |
) | |
) | |
) | |
) | |
(set_local $cx | |
(i32.add | |
(get_local $cx) | |
(i32.const 1) | |
) | |
) | |
(br $for-in5) | |
) | |
) | |
) | |
(set_local $cy | |
(i32.add | |
(get_local $cy) | |
(i32.const 1) | |
) | |
) | |
(br $for-in3) | |
) | |
) | |
) | |
(f64.store | |
(i32.add | |
(get_local $doffs) | |
(i32.shl | |
(i32.add | |
(i32.mul | |
(get_local $y) | |
(get_local $w) | |
) | |
(get_local $x) | |
) | |
(i32.const 3) | |
) | |
) | |
(get_local $s) | |
) | |
) | |
(set_local $x | |
(i32.add | |
(get_local $x) | |
(i32.const 1) | |
) | |
) | |
(br $for-in1) | |
) | |
) | |
) | |
(set_local $y | |
(i32.add | |
(get_local $y) | |
(i32.const 1) | |
) | |
) | |
(br $for-in) | |
) | |
) | |
) | |
) | |
) |
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<!doctype html> | |
<html> | |
<head> | |
<meta charset="utf-8" /> | |
<script src="script-asm.js" defer="defer"></script> | |
</head> | |
<body> | |
</body> | |
</html> |
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<!doctype html> | |
<html> | |
<head> | |
<meta charset="utf-8" /> | |
<script src="script-es6.js" defer="defer"></script> | |
</head> | |
<body> | |
</body> | |
</html> |
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<!doctype html> | |
<html> | |
<head> | |
<meta charset="utf-8" /> | |
<script src="script-wasm.js" defer="defer"></script> | |
</head> | |
<body> | |
</body> | |
</html> |
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"use strct"; | |
// Turing Pattern Simulator program | |
const { | |
w = 200, s = 2, // w: cell size, s: rect size | |
ra = 3, ri = 7, //ra/ri: radius as activator/inhibitor | |
} = Function(`return {${location.hash.slice(1)}}`)(); | |
function force(r) { | |
const w = r * 2 + 1; | |
//return [...Array(w * w)].map((_, i) => 1 / (w * w)); | |
const conv = [...Array(w * w)].map((_, i) => { | |
const x = i % w - r, y = (i / w | 0) - r; | |
return Math.max((r + 1 / 2) - Math.hypot(x, y), 0) ** 2; | |
}); | |
const total = conv.reduce((s, f) => s + f, 0); | |
return conv.map(f => f / total); | |
} | |
const convA = force(ra); | |
const convI = force(ri); | |
// cell automaton | |
function init() { | |
const cells = [...Array(w * w)].map((_, i) => i); | |
return {F: cells.map(i => Math.random())}; | |
} | |
// visualize | |
function render(c2d, {F}) { | |
c2d.clearRect(0, 0, c2d.canvas.width, c2d.canvas.height); | |
F.forEach((v, i) => { | |
const x = i % w, y = i / w | 0; | |
c2d.fillStyle = `hsl(0, 0%, ${clamp(v, 0, 1) * 100}%)`; | |
c2d.fillRect(x * s, y * s, s, s); | |
}); | |
} | |
const canvas = document.createElement("canvas"); | |
canvas.width = canvas.height = w * s; | |
document.body.appendChild(canvas); | |
const c2d = canvas.getContext("2d"); | |
// utils | |
function clamp(v, min, max) { | |
return Math.min(Math.max(min, v), max); | |
} | |
fetch("./conv.asm.js").then(res => res.text()). | |
then(src => Function(`return (${src})`)()). | |
then(asm => { | |
const atleast = (convA.length + convI.length + w * w * 3) << 3; | |
let size = 0x100000; | |
while (size < atleast) size += 0x100000; | |
const heap = {buffer: new ArrayBuffer(size)}; | |
const {conv} = asm(top, {}, heap.buffer); | |
let offs = 0; | |
const cA = new Float64Array(heap.buffer, offs, convA.length); | |
cA.set(convA); | |
offs += cA.byteLength; | |
const cI = new Float64Array(heap.buffer, offs, convI.length); | |
cI.set(convI); | |
offs += cI.byteLength; | |
const sF = new Float64Array(heap.buffer, offs, w * w); | |
offs += sF.byteLength; | |
const dA = new Float64Array(heap.buffer, offs, w * w); | |
offs += dA.byteLength; | |
const dI = new Float64Array(heap.buffer, offs, w * w); | |
function next({F}) { | |
sF.set(F); | |
conv(cA.byteOffset, ra, sF.byteOffset, w, w, dA.byteOffset); | |
conv(cI.byteOffset, ri, sF.byteOffset, w, w, dI.byteOffset); | |
return {F: F.map((v, i) => v + dA[i] - dI[i])}; | |
} | |
// main loop | |
function loop(c2d, channel) { | |
render(c2d, channel); | |
console.time("next"); | |
const n = next(channel); | |
console.timeEnd("next"); | |
requestAnimationFrame(_ => loop(c2d, n)); | |
} | |
loop(c2d, init()); | |
}); |
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"use strct"; | |
// Turing Pattern Simulator program | |
const { | |
w = 200, s = 2, // w: cell size, s: rect size | |
ra = 3, ri = 7, //ra/ri: radius as activator/inhibitor | |
} = Function(`return {${location.hash.slice(1)}}`)(); | |
// convolution for cell array | |
function get(ch, x, y) { | |
return ch[((y + w) % w) * w + ((x + w) % w)]; | |
//return ch[clamp(y, 0, w - 1) * w + clamp(x, 0, w - 1)]; | |
} | |
function conv(f) { | |
return (v, i, ch) => { | |
const x = i % w, y = i / w | 0; | |
return f.reduce((s, c) => s + c.f * get(ch, x + c.x, y + c.y), 0); | |
}; | |
} | |
function force(r) { | |
const w = r * 2 + 1; | |
//return [...Array(w * w)].map( | |
// (_, i) => ({x: i % w - r, y: (i / w | 0) - r, f: 1 / (w * w)})); | |
const conv = [...Array(w * w)].map((_, i) => { | |
const x = i % w - r, y = (i / w | 0) - r; | |
const f = Math.max((r + 1 / 2) - Math.hypot(x, y), 0) ** 2; | |
return {x, y, f}; | |
}).filter(({f}) => f > 0); | |
const total = conv.reduce((s, {f}) => s + f, 0); | |
return conv.map(({x, y, f}) => ({x, y, f: f / total})); | |
} | |
const convA = conv(force(ra)); | |
const convI = conv(force(ri)); | |
// cell automaton | |
function init() { | |
const cells = [...Array(w * w)].map((_, i) => i); | |
return {F: cells.map(i => Math.random())}; | |
} | |
function next({F}) { | |
const A = F.map(convA), I = F.map(convI); | |
return {F: F.map((v, i) => v + A[i] - I[i])}; | |
} | |
// visualize | |
function render(c2d, {F}) { | |
c2d.clearRect(0, 0, c2d.canvas.width, c2d.canvas.height); | |
F.forEach((v, i) => { | |
const x = i % w, y = i / w | 0; | |
c2d.fillStyle = `hsl(0, 0%, ${clamp(v, 0, 1) * 100}%)`; | |
c2d.fillRect(x * s, y * s, s, s); | |
}); | |
} | |
const canvas = document.createElement("canvas"); | |
canvas.width = canvas.height = w * s; | |
document.body.appendChild(canvas); | |
const c2d = canvas.getContext("2d"); | |
loop(c2d, init()); | |
// utils | |
function clamp(v, min, max) { | |
return Math.min(Math.max(min, v), max); | |
} | |
// main loop | |
function loop(c2d, channel) { | |
render(c2d, channel); | |
console.time("next"); | |
const n = next(channel); | |
console.timeEnd("next"); | |
requestAnimationFrame(_ => loop(c2d, n)); | |
} |
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"use strct"; | |
// Turing Pattern Simulator program | |
const { | |
w = 200, s = 2, // w: cell size, s: rect size | |
ra = 3, ri = 7, //ra/ri: radius as activator/inhibitor | |
} = Function(`return {${location.hash.slice(1)}}`)(); | |
function force(r) { | |
const w = r * 2 + 1; | |
const conv = [...Array(w * w)].map((_, i) => { | |
const x = i % w - r, y = (i / w | 0) - r; | |
return Math.max((r + 1 / 2) - Math.hypot(x, y), 0) ** 2; | |
}); | |
const total = conv.reduce((s, f) => s + f, 0); | |
return conv.map(f => f / total); | |
} | |
const convA = force(ra); | |
const convI = force(ri); | |
// cell automaton | |
function init() { | |
const cells = [...Array(w * w)].map((_, i) => i); | |
return {F: cells.map(i => Math.random())}; | |
} | |
// visualize | |
function render(c2d, {F}) { | |
c2d.clearRect(0, 0, c2d.canvas.width, c2d.canvas.height); | |
F.forEach((v, i) => { | |
const x = i % w, y = i / w | 0; | |
c2d.fillStyle = `hsl(0, 0%, ${clamp(v, 0, 1) * 100}%)`; | |
c2d.fillRect(x * s, y * s, s, s); | |
}); | |
} | |
const canvas = document.createElement("canvas"); | |
canvas.width = canvas.height = w * s; | |
document.body.appendChild(canvas); | |
const c2d = canvas.getContext("2d"); | |
// utils | |
function clamp(v, min, max) { | |
return Math.min(Math.max(min, v), max); | |
} | |
fetch("./conv.wasm").then(res => res.arrayBuffer()). | |
then(buf => WebAssembly.instantiate(buf, {})). | |
then(({instance}) => { | |
const {conv, heap} = instance.exports; | |
const size = (convA.length + convI.length + w * w * 3) << 3; | |
while (heap.buffer.byteLength < size) heap.grow(1); | |
let offs = 0; | |
const cA = new Float64Array(heap.buffer, offs, convA.length); | |
cA.set(convA); | |
offs += cA.byteLength; | |
const cI = new Float64Array(heap.buffer, offs, convI.length); | |
cI.set(convI); | |
offs += cI.byteLength; | |
const sF = new Float64Array(heap.buffer, offs, w * w); | |
offs += sF.byteLength; | |
const dA = new Float64Array(heap.buffer, offs, w * w); | |
offs += dA.byteLength; | |
const dI = new Float64Array(heap.buffer, offs, w * w); | |
function next({F}) { | |
sF.set(F); | |
conv(cA.byteOffset, ra, sF.byteOffset, w, w, dA.byteOffset); | |
conv(cI.byteOffset, ri, sF.byteOffset, w, w, dI.byteOffset); | |
return {F: F.map((v, i) => v + dA[i] - dI[i])}; | |
} | |
// main loop | |
function loop(c2d, channel) { | |
render(c2d, channel); | |
console.time("next"); | |
const n = next(channel); | |
console.timeEnd("next"); | |
requestAnimationFrame(_ => loop(c2d, n)); | |
} | |
loop(c2d, init()); | |
}); |
Demo links: benchmark printed on Web Console
- Pure ES6: https://gist.githack.com/bellbind/69e33d31ffa074b4944040deefccedbc/raw/index-es6.html
- WebAssembly: https://gist.githack.com/bellbind/69e33d31ffa074b4944040deefccedbc/raw/index-wasm.html
- asm.js: https://gist.githack.com/bellbind/69e33d31ffa074b4944040deefccedbc/raw/index-asm.html
Benchmark Results:
- firefox-54.0.1 and chrome-59.0.3071.115 on macOS 10.12.5: MacBook Pro (13-inch, Late 2016, Two Thunderbolt 3 ports)
firfox-54 | chrome-59 | |
---|---|---|
ES6 | 70ms | 240ms |
wasm | 160ms | 170ms |
asm.js | 160ms | 400ms |
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"binaryen" 33 toolset(
asm2wasm,
wasm-as
) used as:asm2wasm conv.asm.js > conv-asm.wast
wasm-as conv.wast > conv.wasm
NOTE: The
conv.wast
is based on theasm2wasm conv.asm.js
output.import
, and addexport
memory
$i32u-rem
func
, and replace itscall
part withi32.rem_u
operation in$get
body.