mirror of
https://github.com/ClusterCockpit/cc-backend
synced 2025-11-20 08:47:22 +01:00
667 lines
20 KiB
Svelte
667 lines
20 KiB
Svelte
<!--
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@component Main cluster status view component; renders current system-usage information
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Properties:
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- `presetCluster String`: The cluster to show status information for
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-->
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<script>
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import {
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Row,
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Col,
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Card,
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CardHeader,
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CardTitle,
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CardBody,
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Table,
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Progress,
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Icon,
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} from "@sveltestrap/sveltestrap";
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import {
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queryStore,
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gql,
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getContextClient,
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} from "@urql/svelte";
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import {
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init,
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} from "../generic/utils.js";
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import { formatDurationTime } from "../generic/units.js";
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import Refresher from "../generic/helper/Refresher.svelte";
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import TimeSelection from "../generic/select/TimeSelection.svelte";
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import Roofline from "../generic/plots/Roofline.svelte";
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import Pie, { colors } from "../generic/plots/Pie.svelte";
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import Stacked from "../generic/plots/Stacked.svelte";
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/* Svelte 5 Props */
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let {
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presetCluster,
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useCbColors = false,
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useAltColors = false,
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} = $props();
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/* Const Init */
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const { query: initq } = init();
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const client = getContextClient();
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/* State Init */
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let cluster = $state(presetCluster);
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let pieWidth = $state(0);
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let stackedWidth1 = $state(0);
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let stackedWidth2 = $state(0);
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let plotWidths = $state([]);
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let from = $state(new Date(Date.now() - 5 * 60 * 1000));
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let to = $state(new Date(Date.now()));
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let stackedFrom = $state(Math.floor(Date.now() / 1000) - 14400);
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// Bar Gauges
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let allocatedNodes = $state({});
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let allocatedAccs = $state({});
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let flopRate = $state({});
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let flopRateUnitPrefix = $state({});
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let flopRateUnitBase = $state({});
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let memBwRate = $state({});
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let memBwRateUnitPrefix = $state({});
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let memBwRateUnitBase = $state({});
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// Plain Infos
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let runningJobs = $state({});
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let activeUsers = $state({});
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let totalAccs = $state({});
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/* Derived */
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// Accumulated NodeStates for Piecharts
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const nodesStateCounts = $derived(queryStore({
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client: client,
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query: gql`
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query ($filter: [NodeFilter!]) {
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nodeStates(filter: $filter) {
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state
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count
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}
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}
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`,
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variables: {
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filter: { cluster: { eq: cluster }}
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},
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}));
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const refinedStateData = $derived.by(() => {
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return $nodesStateCounts?.data?.nodeStates.
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filter((e) => ['allocated', 'reserved', 'idle', 'mixed','down', 'unknown'].includes(e.state)).
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sort((a, b) => b.count - a.count)
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});
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const refinedHealthData = $derived.by(() => {
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return $nodesStateCounts?.data?.nodeStates.
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filter((e) => ['full', 'partial', 'failed'].includes(e.state)).
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sort((a, b) => b.count - a.count)
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});
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// States for Stacked charts
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const statesTimed = $derived(queryStore({
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client: client,
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query: gql`
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query ($filter: [NodeFilter!], $typeNode: String!, $typeHealth: String!) {
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nodeStates: nodeStatesTimed(filter: $filter, type: $typeNode) {
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state
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counts
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times
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}
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healthStates: nodeStatesTimed(filter: $filter, type: $typeHealth) {
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state
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counts
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times
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}
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}
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`,
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variables: {
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filter: { cluster: { eq: cluster }, timeStart: 1760097059}, // stackedFrom
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typeNode: "node",
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typeHealth: "health"
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},
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}));
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// Note: nodeMetrics are requested on configured $timestep resolution
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// Result: The latest 5 minutes (datapoints) for each node independent of job
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const statusQuery = $derived(queryStore({
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client: client,
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query: gql`
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query (
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$cluster: String!
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$metrics: [String!]
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$from: Time!
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$to: Time!
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$jobFilter: [JobFilter!]!
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$nodeFilter: [NodeFilter!]!
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$paging: PageRequest!
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$sorting: OrderByInput!
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) {
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# Node 5 Minute Averages for Roofline
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nodeMetrics(
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cluster: $cluster
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metrics: $metrics
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from: $from
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to: $to
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) {
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host
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subCluster
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metrics {
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name
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metric {
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series {
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statistics {
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avg
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}
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}
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}
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}
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}
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# Running Job Metric Average for Rooflines
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jobsMetricStats(filter: $jobFilter, metrics: $metrics) {
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id
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jobId
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duration
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numNodes
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numAccelerators
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subCluster
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stats {
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name
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data {
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avg
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}
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}
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}
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# Get Jobs for Per-Node Counts
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jobs(filter: $jobFilter, order: $sorting, page: $paging) {
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items {
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jobId
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resources {
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hostname
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}
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}
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count
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}
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# Only counts shared nodes once
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allocatedNodes(cluster: $cluster) {
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name
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count
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}
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# Get States for Node Roofline; $sorting unused in backend: Use placeholder
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nodes(filter: $nodeFilter, order: $sorting) {
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count
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items {
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hostname
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cluster
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subCluster
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nodeState
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}
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}
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# totalNodes includes multiples if shared jobs
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jobsStatistics(
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filter: $jobFilter
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page: $paging
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sortBy: TOTALJOBS
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groupBy: SUBCLUSTER
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) {
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id
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totalJobs
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totalUsers
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totalAccs
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}
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}
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`,
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variables: {
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cluster: cluster,
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metrics: ["flops_any", "mem_bw"], // Fixed names for roofline and status bars
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from: from.toISOString(),
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to: to.toISOString(),
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jobFilter: [{ state: ["running"] }, { cluster: { eq: cluster } }],
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nodeFilter: { cluster: { eq: cluster }},
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paging: { itemsPerPage: -1, page: 1 }, // Get all: -1
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sorting: { field: "startTime", type: "col", order: "DESC" }
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},
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requestPolicy: "network-only"
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}));
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/* Effects */
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$effect(() => {
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if ($initq.data && $statusQuery.data) {
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let subClusters = $initq.data.clusters.find(
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(c) => c.name == cluster,
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).subClusters;
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for (let subCluster of subClusters) {
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// Allocations
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allocatedNodes[subCluster.name] =
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$statusQuery.data.allocatedNodes.find(
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({ name }) => name == subCluster.name,
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)?.count || 0;
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allocatedAccs[subCluster.name] =
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$statusQuery.data.jobsStatistics.find(
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({ id }) => id == subCluster.name,
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)?.totalAccs || 0;
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// Infos
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activeUsers[subCluster.name] =
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$statusQuery.data.jobsStatistics.find(
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({ id }) => id == subCluster.name,
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)?.totalUsers || 0;
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runningJobs[subCluster.name] =
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$statusQuery.data.jobsStatistics.find(
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({ id }) => id == subCluster.name,
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)?.totalJobs || 0;
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totalAccs[subCluster.name] =
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(subCluster?.numberOfNodes * subCluster?.topology?.accelerators?.length) || null;
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// Keymetrics
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flopRate[subCluster.name] =
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Math.floor(
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sumUp($statusQuery.data.nodeMetrics, subCluster.name, "flops_any") *
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100,
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) / 100;
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flopRateUnitPrefix[subCluster.name] = subCluster.flopRateSimd.unit.prefix;
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flopRateUnitBase[subCluster.name] = subCluster.flopRateSimd.unit.base;
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memBwRate[subCluster.name] =
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Math.floor(
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sumUp($statusQuery.data.nodeMetrics, subCluster.name, "mem_bw") * 100,
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) / 100;
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memBwRateUnitPrefix[subCluster.name] =
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subCluster.memoryBandwidth.unit.prefix;
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memBwRateUnitBase[subCluster.name] = subCluster.memoryBandwidth.unit.base;
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}
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}
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});
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/* Const Functions */
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const sumUp = (data, subcluster, metric) =>
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data.reduce(
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(sum, node) =>
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node.subCluster == subcluster
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? sum +
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(node.metrics
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.find((m) => m.name == metric)
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?.metric?.series[0]?.statistics?.avg || 0
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)
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: sum,
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0,
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);
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/* Functions */
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function transformJobsStatsToData(subclusterData) {
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/* c will contain values from 0 to 1 representing the duration */
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let data = null
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const x = [], y = [], c = [], day = 86400.0
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if (subclusterData) {
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for (let i = 0; i < subclusterData.length; i++) {
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const flopsData = subclusterData[i].stats.find((s) => s.name == "flops_any")
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const memBwData = subclusterData[i].stats.find((s) => s.name == "mem_bw")
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const f = flopsData.data.avg
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const m = memBwData.data.avg
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const d = subclusterData[i].duration / day
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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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// Long Jobs > 1 Day: Use max Color
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if (d > 1.0) c.push(1.0)
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else c.push(d)
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}
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} else {
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console.warn("transformJobsStatsToData: metrics for 'mem_bw' and/or 'flops_any' missing!")
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}
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if (x.length > 0 && y.length > 0 && c.length > 0) {
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data = [null, [x, y], c] // for dataformat see roofline.svelte
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}
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return data
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}
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function transformNodesStatsToData(subclusterData) {
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let data = null
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const x = [], y = []
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if (subclusterData) {
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for (let i = 0; i < subclusterData.length; i++) {
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const flopsData = subclusterData[i].metrics.find((s) => s.name == "flops_any")
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const memBwData = subclusterData[i].metrics.find((s) => s.name == "mem_bw")
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const f = flopsData.metric.series[0].statistics.avg
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const m = memBwData.metric.series[0].statistics.avg
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let intensity = f / m
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if (Number.isNaN(intensity) || !Number.isFinite(intensity)) {
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intensity = 0.0 // Set to Float Zero: Will not show in Log-Plot (Always below render limit)
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}
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x.push(intensity)
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y.push(f)
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}
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} else {
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// console.warn("transformNodesStatsToData: metrics for 'mem_bw' and/or 'flops_any' missing!")
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}
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if (x.length > 0 && y.length > 0) {
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data = [null, [x, y]] // for dataformat see roofline.svelte
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}
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return data
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}
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function transformJobsStatsToInfo(subclusterData) {
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if (subclusterData) {
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return subclusterData.map((sc) => { return {id: sc.id, jobId: sc.jobId, numNodes: sc.numNodes, numAcc: sc?.numAccelerators? sc.numAccelerators : 0, duration: formatDurationTime(sc.duration)} })
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} else {
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console.warn("transformJobsStatsToInfo: jobInfo missing!")
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return []
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}
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}
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function transformNodesStatsToInfo(subClusterData) {
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let result = [];
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if (subClusterData) { // && $nodesState?.data) {
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// Use Nodes as Returned from CCMS, *NOT* as saved in DB via SlurmState-API!
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for (let j = 0; j < subClusterData.length; j++) {
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const nodeName = subClusterData[j]?.host ? subClusterData[j].host : "unknown"
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const nodeMatch = $statusQuery?.data?.nodes?.items?.find((n) => n.hostname == nodeName && n.subCluster == subClusterData[j].subCluster);
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const nodeState = nodeMatch?.nodeState ? nodeMatch.nodeState : "notindb"
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let numJobs = 0
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if ($statusQuery?.data) {
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const nodeJobs = $statusQuery?.data?.jobs?.items?.filter((job) => job.resources.find((res) => res.hostname == nodeName))
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numJobs = nodeJobs?.length ? nodeJobs.length : 0
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}
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result.push({nodeName: nodeName, nodeState: nodeState, numJobs: numJobs})
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};
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};
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return result
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}
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function legendColors(targetIdx) {
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// Reuses first color if targetIdx overflows
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let c;
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if (useCbColors) {
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c = [...colors['colorblind']];
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} else if (useAltColors) {
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c = [...colors['alternative']];
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} else {
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c = [...colors['default']];
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}
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return c[(c.length + targetIdx) % c.length];
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}
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</script>
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<!-- Refresher and space for other options -->
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<Row class="justify-content-between">
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<Col xs="12" md="5" lg="4" xl="3">
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<TimeSelection
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customEnabled={false}
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applyTime={(newFrom, newTo) => {
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stackedFrom = Math.floor(newFrom.getTime() / 1000);
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}}
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/>
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</Col>
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<Col xs="12" md="5" lg="4" xl="3">
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<Refresher
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initially={120}
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onRefresh={() => {
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from = new Date(Date.now() - 5 * 60 * 1000);
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to = new Date(Date.now());
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}}
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/>
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</Col>
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</Row>
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<hr/>
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<!-- Node Stack Charts Dev-->
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{#if $initq.data && $statesTimed.data}
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<Row cols={{ md: 2 , sm: 1}} class="mb-3 justify-content-center">
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<Col class="px-3 mt-2 mt-lg-0">
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<div bind:clientWidth={stackedWidth1}>
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{#key $statesTimed?.data?.nodeStates}
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<h4 class="text-center">
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{cluster.charAt(0).toUpperCase() + cluster.slice(1)} Node States Over Time
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</h4>
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<Stacked
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data={$statesTimed?.data?.nodeStates}
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width={stackedWidth1 * 0.95}
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xLabel="Time"
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yLabel="Nodes"
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yunit = "#Count"
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title = "Node States"
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stateType = "Node"
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/>
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{/key}
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</div>
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</Col>
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<Col class="px-3 mt-2 mt-lg-0">
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<div bind:clientWidth={stackedWidth2}>
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{#key $statesTimed?.data?.healthStates}
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<h4 class="text-center">
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{cluster.charAt(0).toUpperCase() + cluster.slice(1)} Health States Over Time
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</h4>
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<Stacked
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data={$statesTimed?.data?.healthStates}
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width={stackedWidth2 * 0.95}
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xLabel="Time"
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yLabel="Nodes"
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yunit = "#Count"
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title = "Health States"
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stateType = "Health"
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/>
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{/key}
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</div>
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</Col>
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</Row>
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{/if}
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<hr/>
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<!-- Node Health Pis, later Charts -->
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{#if $initq.data && $nodesStateCounts.data}
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<Row cols={{ lg: 4, md: 2 , sm: 1}} class="mb-3 justify-content-center">
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<Col class="px-3 mt-2 mt-lg-0">
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<div bind:clientWidth={pieWidth}>
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{#key refinedStateData}
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<h4 class="text-center">
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Current {cluster.charAt(0).toUpperCase() + cluster.slice(1)} Node States
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</h4>
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<Pie
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{useAltColors}
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canvasId="hpcpie-slurm"
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size={pieWidth * 0.55}
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sliceLabel="Nodes"
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quantities={refinedStateData.map(
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(sd) => sd.count,
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)}
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entities={refinedStateData.map(
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(sd) => sd.state,
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)}
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/>
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{/key}
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</div>
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</Col>
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<Col class="px-4 py-2">
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{#key refinedStateData}
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<Table>
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<tr class="mb-2">
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<th></th>
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<th>Current State</th>
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<th>Nodes</th>
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</tr>
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{#each refinedStateData as sd, i}
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<tr>
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<td><Icon name="circle-fill" style="color: {legendColors(i)};"/></td>
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<td>{sd.state}</td>
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<td>{sd.count}</td>
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</tr>
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{/each}
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</Table>
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{/key}
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</Col>
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<Col class="px-3 mt-2 mt-lg-0">
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<div bind:clientWidth={pieWidth}>
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{#key refinedHealthData}
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<h4 class="text-center">
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Current {cluster.charAt(0).toUpperCase() + cluster.slice(1)} Node Health
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</h4>
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<Pie
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{useAltColors}
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canvasId="hpcpie-health"
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size={pieWidth * 0.55}
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sliceLabel="Nodes"
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quantities={refinedHealthData.map(
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(sd) => sd.count,
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)}
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entities={refinedHealthData.map(
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(sd) => sd.state,
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)}
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/>
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{/key}
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</div>
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</Col>
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<Col class="px-4 py-2">
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{#key refinedHealthData}
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<Table>
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<tr class="mb-2">
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<th></th>
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<th>Current Health</th>
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<th>Nodes</th>
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</tr>
|
|
{#each refinedHealthData as hd, i}
|
|
<tr>
|
|
<td><Icon name="circle-fill" style="color: {legendColors(i)};" /></td>
|
|
<td>{hd.state}</td>
|
|
<td>{hd.count}</td>
|
|
</tr>
|
|
{/each}
|
|
</Table>
|
|
{/key}
|
|
</Col>
|
|
</Row>
|
|
{/if}
|
|
|
|
<hr/>
|
|
<!-- Gauges & Roofline per Subcluster-->
|
|
{#if $initq.data && $statusQuery.data}
|
|
{#each $initq.data.clusters.find((c) => c.name == cluster).subClusters as subCluster, i}
|
|
<Row cols={{ lg: 3, md: 1 , sm: 1}} class="mb-3 justify-content-center">
|
|
<Col class="px-3">
|
|
<Card class="h-auto mt-1">
|
|
<CardHeader>
|
|
<CardTitle class="mb-0">SubCluster "{subCluster.name}"</CardTitle>
|
|
<span>{subCluster.processorType}</span>
|
|
</CardHeader>
|
|
<CardBody>
|
|
<Table borderless>
|
|
<tr class="py-2">
|
|
<td style="font-size:x-large;">{runningJobs[subCluster.name]} Running Jobs</td>
|
|
<td colspan="2" style="font-size:x-large;">{activeUsers[subCluster.name]} Active Users</td>
|
|
</tr>
|
|
<hr class="my-1"/>
|
|
<tr class="pt-2">
|
|
<td style="font-size: large;">
|
|
Flop Rate (<span style="cursor: help;" title="Flops[Any] = (Flops[Double] x 2) + Flops[Single]">Any</span>)
|
|
</td>
|
|
<td colspan="2" style="font-size: large;">
|
|
Memory BW Rate
|
|
</td>
|
|
</tr>
|
|
<tr class="pb-2">
|
|
<td style="font-size:x-large;">
|
|
{flopRate[subCluster.name]}
|
|
{flopRateUnitPrefix[subCluster.name]}{flopRateUnitBase[subCluster.name]}
|
|
</td>
|
|
<td colspan="2" style="font-size:x-large;">
|
|
{memBwRate[subCluster.name]}
|
|
{memBwRateUnitPrefix[subCluster.name]}{memBwRateUnitBase[subCluster.name]}
|
|
</td>
|
|
</tr>
|
|
<hr class="my-1"/>
|
|
<tr class="py-2">
|
|
<th scope="col">Allocated Nodes</th>
|
|
<td style="min-width: 100px;"
|
|
><div class="col">
|
|
<Progress
|
|
value={allocatedNodes[subCluster.name]}
|
|
max={subCluster.numberOfNodes}
|
|
/>
|
|
</div></td
|
|
>
|
|
<td
|
|
>{allocatedNodes[subCluster.name]} / {subCluster.numberOfNodes}
|
|
Nodes</td
|
|
>
|
|
</tr>
|
|
{#if totalAccs[subCluster.name] !== null}
|
|
<tr class="py-2">
|
|
<th scope="col">Allocated Accelerators</th>
|
|
<td style="min-width: 100px;"
|
|
><div class="col">
|
|
<Progress
|
|
value={allocatedAccs[subCluster.name]}
|
|
max={totalAccs[subCluster.name]}
|
|
/>
|
|
</div></td
|
|
>
|
|
<td
|
|
>{allocatedAccs[subCluster.name]} / {totalAccs[subCluster.name]}
|
|
Accelerators</td
|
|
>
|
|
</tr>
|
|
{/if}
|
|
</Table>
|
|
</CardBody>
|
|
</Card>
|
|
</Col>
|
|
<Col class="px-3 mt-2 mt-lg-0">
|
|
<div bind:clientWidth={plotWidths[i]}>
|
|
{#key $statusQuery?.data?.nodeMetrics}
|
|
<Roofline
|
|
useColors={true}
|
|
allowSizeChange
|
|
width={plotWidths[i] - 10}
|
|
height={300}
|
|
cluster={cluster}
|
|
subCluster={subCluster}
|
|
roofData={transformNodesStatsToData($statusQuery?.data?.nodeMetrics.filter(
|
|
(data) => data.subCluster == subCluster.name,
|
|
)
|
|
)}
|
|
nodesData={transformNodesStatsToInfo($statusQuery?.data?.nodeMetrics.filter(
|
|
(data) => data.subCluster == subCluster.name,
|
|
)
|
|
)}
|
|
/>
|
|
{/key}
|
|
</div>
|
|
</Col>
|
|
<Col class="px-3 mt-2 mt-lg-0">
|
|
<div bind:clientWidth={plotWidths[i]}>
|
|
{#key $statusQuery?.data?.jobsMetricStats}
|
|
<Roofline
|
|
useColors={true}
|
|
allowSizeChange
|
|
width={plotWidths[i] - 10}
|
|
height={300}
|
|
subCluster={subCluster}
|
|
roofData={transformJobsStatsToData($statusQuery?.data?.jobsMetricStats.filter(
|
|
(data) => data.subCluster == subCluster.name,
|
|
)
|
|
)}
|
|
jobsData={transformJobsStatsToInfo($statusQuery?.data?.jobsMetricStats.filter(
|
|
(data) => data.subCluster == subCluster.name,
|
|
)
|
|
)}
|
|
/>
|
|
{/key}
|
|
</div>
|
|
</Col>
|
|
</Row>
|
|
{/each}
|
|
{:else}
|
|
<Card class="mx-4" body color="warning">Cannot render status rooflines: No data!</Card>
|
|
{/if}
|