"use client"; import { useState, useEffect } from "react"; import { motion } from "framer-motion"; type NodeStatus = "ACTIVE" | "IDLE" | "OVERLOADED" | "FAILED"; interface GPUNode { id: string; utilization: number; memory: number; load: number; status: NodeStatus; } interface GPUClusterPanelProps { sessionId?: string; mode?: string; gpuPool?: any[]; // Live data from observation } export default function GPUClusterPanel({ sessionId, mode, gpuPool }: GPUClusterPanelProps) { const [mounted, setMounted] = useState(false); const [nodes, setNodes] = useState([ { id: "GPU-1", utilization: 0, memory: 0, load: 0, status: "IDLE" }, { id: "GPU-2", utilization: 0, memory: 0, load: 0, status: "IDLE" }, { id: "GPU-3", utilization: 0, memory: 0, load: 0, status: "IDLE" }, { id: "GPU-4", utilization: 0, memory: 0, load: 0, status: "IDLE" }, ]); const [avgLoad, setAvgLoad] = useState(0); const [jitter, setJitter] = useState(0.45); useEffect(() => { setMounted(true); }, []); // ── LIVE SYNC FROM OBSERVATION ──────────────────────────── useEffect(() => { if (gpuPool && Array.isArray(gpuPool)) { setNodes(gpuPool.slice(0, 4).map((g: any) => { const util = (g.memory_used / g.memory_total) * 100; let status = g.state.toUpperCase(); if (status === "ALLOCATED") status = "ACTIVE"; return { id: g.id, utilization: util, memory: util, load: (util / 100) * 4.2, status: status as NodeStatus }; })); } else if (!sessionId || mode !== "cluster") { // Fallback to subtle idle simulation if no live data const timer = setInterval(() => { setJitter(Math.random() * 0.5); setNodes(prev => prev.map(n => ({ ...n, utilization: Math.max(0, n.utilization + (Math.random() - 0.5) * 2), load: n.utilization * 0.04 }))); }, 2000); return () => clearInterval(timer); } }, [gpuPool, sessionId, mode]); useEffect(() => { const total = nodes.reduce((acc, n) => acc + n.utilization, 0); setAvgLoad(total / nodes.length); }, [nodes]); if (!mounted) return null; return (
03 // COMPUTE RESOURCES

GPU Compute Clusters

Real-time telemetry from the underlying inference hardware. Note how cluster utilization spikes as the RL model allocates worker jobs.

{nodes.map((node) => (
{node.id} // CORE-AX-{node.id.split("-")[1] || "0X"}
{node.status}
UTILIZATION {Math.round(node.utilization)}%
90 ? "var(--red)" : "var(--cyan)" } as any} />
MEMORY USAGE {Math.round(node.memory)}%
COMPUTE {node.load.toFixed(1)} TFLOPS
TEMP {Math.round(40 + (node.utilization * 0.4))}°C
))}
TOTAL CLUSTER LOAD
80 ? "var(--red)" : "var(--cyan)", color: avgLoad > 80 ? "var(--red)" : "var(--cyan)" } as any} />
{Math.round(avgLoad)}%
THROUGHPUT: {Math.round(140 - (avgLoad * 0.5))} FPS LATENCY: {Math.round(12 + (avgLoad * 0.2))}ms JITTER: {jitter.toFixed(2)}ms
); }