cc-backend/web/frontend/src/Status.root.svelte

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<script>
import Refresher from './joblist/Refresher.svelte'
import Roofline, { transformPerNodeData } from './plots/Roofline.svelte'
import Histogram from './plots/Histogram.svelte'
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import { Row, Col, Spinner, Card, CardHeader, CardTitle, CardBody, Table, Progress, Icon } from 'sveltestrap'
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import { init } from './utils.js'
import { scaleNumbers } from './units.js'
import { queryStore, gql, getContextClient } from '@urql/svelte'
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const { query: initq } = init()
export let cluster
let plotWidths = [], colWidth1 = 0, colWidth2
let from = new Date(Date.now() - 5 * 60 * 1000), to = new Date(Date.now())
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const client = getContextClient();
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$: mainQuery = queryStore({
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client: client,
query: gql`query($cluster: String!, $filter: [JobFilter!]!, $metrics: [String!], $from: Time!, $to: Time!) {
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nodeMetrics(cluster: $cluster, metrics: $metrics, from: $from, to: $to) {
host
subCluster
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metrics {
name
scope
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metric {
timestep
unit { base, prefix }
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series { data }
}
}
}
stats: jobsStatistics(filter: $filter) {
histDuration { count, value }
histNumNodes { count, value }
}
allocatedNodes(cluster: $cluster) { name, count }
topUsers: jobsCount(filter: $filter, groupBy: USER, weight: NODE_COUNT, limit: 10) { name, count }
topProjects: jobsCount(filter: $filter, groupBy: PROJECT, weight: NODE_COUNT, limit: 10) { name, count }
}`,
variables: {
cluster: cluster, metrics: ['flops_any', 'mem_bw'], from: from.toISOString(), to: to.toISOString(),
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filter: [{ state: ['running'] }, { cluster: { eq: cluster } }]
}
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})
const sumUp = (data, subcluster, metric) => data.reduce((sum, node) => node.subCluster == subcluster
? sum + (node.metrics.find(m => m.name == metric)?.metric.series.reduce((sum, series) => sum + series.data[series.data.length - 1], 0) || 0)
: sum, 0)
let allocatedNodes = {}, flopRate = {}, flopRateUnitPrefix = {}, flopRateUnitBase = {}, memBwRate = {}, memBwRateUnitPrefix = {}, memBwRateUnitBase = {}
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$: if ($initq.data && $mainQuery.data) {
let subClusters = $initq.data.clusters.find(c => c.name == cluster).subClusters
for (let subCluster of subClusters) {
allocatedNodes[subCluster.name] = $mainQuery.data.allocatedNodes.find(({ name }) => name == subCluster.name)?.count || 0
flopRate[subCluster.name] = Math.floor(sumUp($mainQuery.data.nodeMetrics, subCluster.name, 'flops_any') * 100) / 100
flopRateUnitPrefix[subCluster.name] = subCluster.flopRateSimd.unit.prefix
flopRateUnitBase[subCluster.name] = subCluster.flopRateSimd.unit.base
memBwRate[subCluster.name] = Math.floor(sumUp($mainQuery.data.nodeMetrics, subCluster.name, 'mem_bw') * 100) / 100
memBwRateUnitPrefix[subCluster.name] = subCluster.memoryBandwidth.unit.prefix
memBwRateUnitBase[subCluster.name] = subCluster.memoryBandwidth.unit.base
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}
}
</script>
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<!-- Loading indicator & Refresh -->
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<Row>
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<Col xs="auto" style="align-self: flex-end;">
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<h4 class="mb-0" >Current utilization of cluster "{cluster}"</h4>
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</Col>
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<Col xs="auto">
{#if $initq.fetching || $mainQuery.fetching}
<Spinner/>
{:else if $initq.error}
<Card body color="danger">{$initq.error.message}</Card>
{:else}
<!-- ... -->
{/if}
</Col>
<Col xs="auto" style="margin-left: auto;">
<Refresher initially={120} on:reload={() => {
from = new Date(Date.now() - 5 * 60 * 1000)
to = new Date(Date.now())
}} />
</Col>
</Row>
{#if $mainQuery.error}
<Row>
<Col>
<Card body color="danger">{$mainQuery.error.message}</Card>
</Col>
</Row>
{/if}
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<hr>
<!-- Gauges & Roofline per Subcluster-->
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{#if $initq.data && $mainQuery.data}
{#each $initq.data.clusters.find(c => c.name == cluster).subClusters as subCluster, i}
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<Row cols={2} class="mb-3 justify-content-center">
<Col xs="4" class="px-3">
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<Card class="h-auto mt-1">
<CardHeader>
<CardTitle class="mb-0">SubCluster "{subCluster.name}"</CardTitle>
</CardHeader>
<CardBody>
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<Table borderless>
<tr class="py-2">
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<th scope="col">Allocated Nodes</th>
<td style="min-width: 100px;"><div class="col"><Progress value={allocatedNodes[subCluster.name]} max={subCluster.numberOfNodes}/></div></td>
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<td>{allocatedNodes[subCluster.name]} / {subCluster.numberOfNodes} Nodes</td>
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</tr>
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<tr class="py-2">
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<th scope="col">Flop Rate (Any) <Icon name="info-circle" class="p-1" style="cursor: help;" title="Flops[Any] = (Flops[Double] x 2) + Flops[Single]"/></th>
<td style="min-width: 100px;"><div class="col"><Progress value={flopRate[subCluster.name]} max={subCluster.flopRateSimd.value * subCluster.numberOfNodes}/></div></td>
<td>
{scaleNumbers(flopRate[subCluster.name],
(subCluster.flopRateSimd.value * subCluster.numberOfNodes),
flopRateUnitPrefix[subCluster.name])
}{flopRateUnitBase[subCluster.name]} [Max]
</td>
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</tr>
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<tr class="py-2">
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<th scope="col">MemBw Rate</th>
<td style="min-width: 100px;"><div class="col"><Progress value={memBwRate[subCluster.name]} max={subCluster.memoryBandwidth.value * subCluster.numberOfNodes}/></div></td>
<td>
{scaleNumbers(memBwRate[subCluster.name],
(subCluster.memoryBandwidth.value * subCluster.numberOfNodes),
memBwRateUnitPrefix[subCluster.name])
}{memBwRateUnitBase[subCluster.name]} [Max]
</td>
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</tr>
</Table>
</CardBody>
</Card>
</Col>
<Col class="px-3">
<div bind:clientWidth={plotWidths[i]}>
{#key $mainQuery.data.nodeMetrics}
<Roofline
width={plotWidths[i] - 10} height={300} colorDots={true} showTime={false} cluster={subCluster}
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data={transformPerNodeData($mainQuery.data.nodeMetrics.filter(data => data.subCluster == subCluster.name))} />
{/key}
</div>
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</Col>
</Row>
{/each}
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<hr style="margin-top: -1em;">
<!-- Usage Stats as Histograms -->
<Row cols={4}>
<Col class="p-2">
<div bind:clientWidth={colWidth1}>
<h4 class="mb-3 text-center">Top Users</h4>
{#key $mainQuery.data}
<Histogram
width={colWidth1 - 25}
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data={$mainQuery.data.topUsers.sort((a, b) => b.count - a.count).map(({ count }, idx) => ({ count, value: idx }))}
label={(x) => x < $mainQuery.data.topUsers.length ? $mainQuery.data.topUsers[Math.floor(x)].name : '0'}
xlabel="User Name" ylabel="Number of Jobs" />
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{/key}
</div>
</Col>
<Col class="px-4 py-2">
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<Table>
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<tr class="mb-2"><th>User Name</th><th>Number of Nodes</th></tr>
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{#each $mainQuery.data.topUsers.sort((a, b) => b.count - a.count) as { name, count }}
<tr>
<th scope="col"><a href="/monitoring/user/{name}?cluster={cluster}&state=running">{name}</a></th>
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<td>{count}</td>
</tr>
{/each}
</Table>
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</Col>
<Col class="p-2">
<h4 class="mb-3 text-center">Top Projects</h4>
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{#key $mainQuery.data}
<Histogram
width={colWidth1 - 25}
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data={$mainQuery.data.topProjects.sort((a, b) => b.count - a.count).map(({ count }, idx) => ({ count, value: idx }))}
label={(x) => x < $mainQuery.data.topProjects.length ? $mainQuery.data.topProjects[Math.floor(x)].name : '0'}
xlabel="Project Code" ylabel="Number of Jobs" />
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{/key}
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</Col>
<Col class="px-4 py-2">
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<Table>
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<tr class="mb-2"><th>Project Code</th><th>Number of Nodes</th></tr>
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{#each $mainQuery.data.topProjects.sort((a, b) => b.count - a.count) as { name, count }}
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<tr>
<th scope="col"><a href="/monitoring/jobs/?cluster={cluster}&state=running&project={name}&projectMatch=eq">{name}</a></th>
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<td>{count}</td>
</tr>
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{/each}
</Table>
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</Col>
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</Row>
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<Row cols={2} class="mt-3">
<Col class="p-2">
<div bind:clientWidth={colWidth2}>
<h4 class="mb-3 text-center">Duration Distribution</h4>
{#key $mainQuery.data.stats}
<Histogram
width={colWidth2 - 25}
data={$mainQuery.data.stats[0].histDuration}
xlabel="Current Runtimes [h]"
ylabel="Number of Jobs" />
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{/key}
</div>
</Col>
<Col class="p-2">
<h4 class="mb-3 text-center">Number of Nodes Distribution</h4>
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{#key $mainQuery.data.stats}
<Histogram
width={colWidth2 - 25}
data={$mainQuery.data.stats[0].histNumNodes}
xlabel="Allocated Nodes [#]"
ylabel="Number of Jobs" />
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{/key}
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</Col>
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</Row>
{/if}