
At the top of the image is the title “AI DATA CENTER AGENT PLATFORM”, outlining a system structured around three lifecycle phases and a Data Utilization sector, all orchestrated by the central ‘AI CORE’.
1. DESIGN (Lifecycle Phase 1)
- Key Role: Determines optimal infrastructure layouts for high-density GPU clusters, 800V HVDC, and BESS.
- Core Technology: Uses CFD and PIML simulations to preemptively eliminate thermal hotspots.
2. CONSTRUCTION (Lifecycle Phase 2)
- Key Role: Automates material procurement scheduling and verifies installation compliance for OCP standard equipment.
- Core Technology: Streamlines the commissioning process to eliminate human errors and enhance deployment efficiency.
3. OPERATIONS (Lifecycle Phase 3)
- Key Role: Executes dynamic power distribution (load balancing) for real-time load fluctuations and optimizes liquid cooling via CDU control.
- Core Technology: Performs predictive maintenance with anomaly detection to preemptively prevent failures.
4. DATA UTILIZATION
- A. ONTOLOGY (Semantic Knowledge Map)
- Defines hierarchical relationships among physical and logical resources (Servers, Racks, PDUs, UPS, Cooling Towers) using semantic modeling.
- Utilizes Graph RAG and topology mapping to trace affected VMs or LLM serving Pods within milliseconds during a failure.
- Integrates heterogeneous equipment data through standardized schemas (DMTF Redfish, Modbus, BACnet).
- B. TELEMETRY (Real-time Streaming Data)
- Collects high-frequency time-series streaming data including temperature, wattage, flow rate, and delta-P.
- Fuses power infrastructure metrics with IT workload metrics to predict thermal and power peaks proactively.
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