mirror of
https://github.com/ClusterCockpit/cc-backend
synced 2024-11-10 00:47:26 +01:00
Render loglog scatter, fix data format, start draw
This commit is contained in:
Christoph Kluge
parent
c1b5134627
commit
8d7f942de4
@ -672,6 +672,7 @@
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<div bind:clientWidth={colWidth3}>
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<Rooflineuplot
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width={colWidth3 - 25}
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cluster={$initq.data.clusters.find((c) => c.name == cluster).subClusters[0]}
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/>
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</Col>
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</Row>
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@ -7,7 +7,7 @@
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export let flopsAny = null
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export let memBw = null
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export let cluster = null
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export let maxY = null
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export let defaultMaxY = null
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export let width = 500
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export let height = 300
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export let tiles = null
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@ -19,6 +19,11 @@
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let uplot = null
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let timeoutId = null
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const paddingLeft = 40,
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paddingRight = 10,
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paddingTop = 10,
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paddingBottom = 50
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// Three Render-Cases:
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// #1 Single-Job Roofline -> Has Time-Information: Use data, allow colorDots && showTime
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// #2 MultiNode Roofline - > Has No Time-Information: Transform from nodeData, only "IST"-state of nodes, no timeInfo
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@ -30,6 +35,14 @@
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return Math.floor(Math.random() * (max - min + 1)) + min;
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}
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function randFloat(min, max) {
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return roundTwo(((Math.random() * (max - min + 1)) + min) / randInt(1, 500));
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}
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function roundTwo(num) {
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return Math.round((num + Number.EPSILON) * 100) / 100
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}
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function filledArr(len, val) {
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let arr = Array(len);
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@ -45,26 +58,42 @@
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return arr;
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}
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let points = 100;
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let series = 2;
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let time = []
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let points = 1000;
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for (let i = 0; i < points; ++i)
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time[i] = i;
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data = filledArr(series, v => [
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filledArr(points, i => randInt(0,200)),
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filledArr(points, i => randInt(0,200)),
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]);
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data[0] = null;
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data = [null, [], []] // Null-Axis required for scatter
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data[1][0] = filledArr(points, i => randFloat(1,5000)) // Intensity
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data[1][1] = filledArr(points, i => randFloat(1,5000)) // Performance
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data[2] = filledArr(points, i => 0) // Time Information (Optional)
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console.log("Subcluster: ", cluster);
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console.log("Data: ", data);
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// End Demo Data
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// Helpers
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const [minX, maxX, minY, maxY] = [0.01, 1000, 1., cluster?.flopRateSimd?.value || defaultMaxY]
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const w = width - paddingLeft - paddingRight
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const h = height - paddingTop - paddingBottom
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const [log10minX, log10maxX, log10minY, log10maxY] =
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[Math.log10(minX), Math.log10(maxX), Math.log10(minY), Math.log10(maxY)]
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const getCanvasX = (x) => {
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x = Math.log10(x)
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x -= log10minX; x /= (log10maxX - log10minX)
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return Math.round((x * w) + paddingLeft)
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}
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const getCanvasY = (y) => {
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y = Math.log10(y)
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y -= log10minY
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y /= (log10maxY - log10minY)
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return Math.round((h - y * h) + paddingTop)
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}
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function getGradientR(x) {
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if (x < 0.5) return 0
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if (x > 0.75) return 255
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@ -90,6 +119,78 @@
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return `rgb(${getGradientR(c)}, ${getGradientG(c)}, ${getGradientB(c)})`
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}
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function lineIntersect(x1, y1, x2, y2, x3, y3, x4, y4) {
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let l = (y4 - y3) * (x2 - x1) - (x4 - x3) * (y2 - y1)
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let a = ((x4 - x3) * (y1 - y3) - (y4 - y3) * (x1 - x3)) / l
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return {
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x: x1 + a * (x2 - x1),
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y: y1 + a * (y2 - y1)
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}
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}
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function transformData(flopsAny, memBw, colorDots) { // Uses Metric Object
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const nodes = flopsAny.series.length
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const timesteps = flopsAny.series[0].data.length
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/* c will contain values from 0 to 1 representing the time */
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const x = [], y = [], c = []
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if (flopsAny && memBw) {
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for (let i = 0; i < nodes; i++) {
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const flopsData = flopsAny.series[i].data
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const memBwData = memBw.series[i].data
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for (let j = 0; j < timesteps; j++) {
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const f = flopsData[j], m = memBwData[j]
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const intensity = f / m
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if (Number.isNaN(intensity) || !Number.isFinite(intensity))
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continue
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x.push(intensity)
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y.push(f)
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c.push(colorDots ? j / timesteps : 0)
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}
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}
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} else {
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console.warn("transformData: metrics for 'mem_bw' and/or 'flops_any' missing!")
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}
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return {
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x, y, c,
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xLabel: 'Intensity [FLOPS/byte]',
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yLabel: 'Performance [GFLOPS]'
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}
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}
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// Return something to be plotted. The argument shall be the result of the
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// `nodeMetrics` GraphQL query.
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export function transformPerNodeData(nodes) {
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const x = [], y = [], c = []
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for (let node of nodes) {
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let flopsAny = node.metrics.find(m => m.name == 'flops_any' && m.scope == 'node')?.metric
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let memBw = node.metrics.find(m => m.name == 'mem_bw' && m.scope == 'node')?.metric
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if (!flopsAny || !memBw) {
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console.warn("transformPerNodeData: metrics for 'mem_bw' and/or 'flops_any' missing!")
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continue
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}
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let flopsData = flopsAny.series[0].data, memBwData = memBw.series[0].data
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const f = flopsData[flopsData.length - 1], m = memBwData[flopsData.length - 1]
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const intensity = f / m
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if (Number.isNaN(intensity) || !Number.isFinite(intensity))
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continue
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x.push(intensity)
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y.push(f)
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c.push(0)
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}
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return {
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x, y, c,
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xLabel: 'Intensity [FLOPS/byte]',
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yLabel: 'Performance [GFLOPS]'
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}
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}
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// End Helpers
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const drawPoints = (u, seriesIdx, idx0, idx1) => {
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@ -123,22 +224,6 @@
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return null;
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};
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function guardedRange(u, min, max) {
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if (max == min) {
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if (min == null) {
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min = 0;
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max = 100;
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}
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else {
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let delta = Math.abs(max) || 100;
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max += delta;
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min -= delta;
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}
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}
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return [min, max];
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}
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function render() {
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const opts = {
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title: "",
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@ -146,8 +231,39 @@
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width: width,
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height: height,
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legend: {
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live: false,
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show: false
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},
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axes: [
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{
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label: 'Intensity [FLOPS/Byte]'
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},
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{
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label: 'Performace [GFLOPS]'
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}
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],
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scales: {
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x: {
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time: false,
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distr: 3,
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log: 10,
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},
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y: {
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distr: 3,
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log: 10,
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},
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},
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series: [
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{},
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{
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stroke: (u, seriesIdx) => {
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for (let i = 0; i < points; ++i) { return getRGB(data[2][i]) }
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},
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fill: (u, seriesIdx) => {
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for (let i = 0; i < points; ++i) { return getRGB(data[2][i]) }
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},
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paths: drawPoints,
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}
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],
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hooks: {
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drawClear: [
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u => {
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@ -157,48 +273,51 @@
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});
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},
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],
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},
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scales: {
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x: {
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time: false,
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// auto: false,
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// range: [0, 500],
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// remove any scale padding, use raw data limits
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range: guardedRange,
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},
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y: {
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// auto: false,
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// range: [0, 500],
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// remove any scale padding, use raw data limits
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range: guardedRange,
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},
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},
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series: [
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{
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/*
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stroke: "red",
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fill: "rgba(255,0,0,0.1)",
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paths: (u, seriesIdx, idx0, idx1) => {
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uPlot.orient(u, seriesIdx, (series, dataX, dataY, scaleX, scaleY, valToPosX, valToPosY, xOff, yOff, xDim, yDim) => {
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let d = u.data[seriesIdx];
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draw: [
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u => { // draw roofs
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u.ctx.strokeStyle = 'black'
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u.ctx.lineWidth = 2
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u.ctx.beginPath()
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if (cluster != null) {
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const ycut = 0.01 * cluster.memoryBandwidth.value
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const scalarKnee = (cluster.flopRateScalar.value - ycut) / cluster.memoryBandwidth.value
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const simdKnee = (cluster.flopRateSimd.value - ycut) / cluster.memoryBandwidth.value
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const scalarKneeX = getCanvasX(scalarKnee),
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simdKneeX = getCanvasX(simdKnee),
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flopRateScalarY = getCanvasY(cluster.flopRateScalar.value),
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flopRateSimdY = getCanvasY(cluster.flopRateSimd.value)
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console.log(d);
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});
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return null;
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},
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*/
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},
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{
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stroke: (u, seriesIdx) => {
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for (let i = 0; i < points; ++i) { return getRGB(time[i]) }
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},
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fill: (u, seriesIdx) => {
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for (let i = 0; i < points; ++i) { return getRGB(time[i]) }
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},
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paths: drawPoints,
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if (scalarKneeX < width - paddingRight) {
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u.ctx.moveTo(scalarKneeX, flopRateScalarY)
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u.ctx.lineTo(width - paddingRight, flopRateScalarY)
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}
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],
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if (simdKneeX < width - paddingRight) {
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u.ctx.moveTo(simdKneeX, flopRateSimdY)
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u.ctx.lineTo(width - paddingRight, flopRateSimdY)
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}
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let x1 = getCanvasX(0.01),
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y1 = getCanvasY(ycut),
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x2 = getCanvasX(simdKnee),
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y2 = flopRateSimdY
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let xAxisIntersect = lineIntersect(
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x1, y1, x2, y2,
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0, height - paddingBottom, width, height - paddingBottom)
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if (xAxisIntersect.x > x1) {
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x1 = xAxisIntersect.x
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y1 = xAxisIntersect.y
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}
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u.ctx.moveTo(x1, y1)
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u.ctx.lineTo(x2, y2)
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}
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u.ctx.stroke()
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}
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]
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},
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};
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uplot = new uPlot(opts, data, plotWrapper);
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