GPU accelerator trays
Parallel processors run the matrix calculations behind AI training and inference.
Live 3D facility explorer
Step inside the
AI factory.
Rotate the campus, zoom into the data hall, and open a rack. Follow animated electricity, fiber traffic, and liquid cooling from the grid to the chips.
REAL-TIME 3DMOUSE + TOUCH
WebGL is unavailable on this device. Use the component index below to explore the facility.
SIMULATED TELEMETRY
12.8MW IT LOAD
1.18PUE
96kW / RACK
DRAG TO ORBIT · SCROLL OR PINCH TO ZOOM · TAP A SYSTEM
01
FACILITY MAP
Trace every critical system
02
RACK CUTAWAY
What lives inside an AI rack
REPRESENTATIVE HIGH-DENSITY RACK
One rack is a complete compute, power, network, and cooling system.
Use “Inside rack” above to fly closer, then explode the trays. The model is educational rather than a replica of one vendor's proprietary design.
CPU & memory hosts
Prepare data, schedule jobs, and coordinate the accelerators in each node.
NVMe & checkpoint storage
Feed datasets quickly and save model state so long training runs can recover.
Top-of-rack switch
Connects servers to the low-latency spine fabric through high-speed optical links.
Dual intelligent PDU
Meters and delivers redundant A/B power to every device in the rack.
Coolant manifold
Splits supply and return flow across cold plates mounted on high-heat chips.
03
ACTIVE INFRASTRUCTURE FLOW
From electricity to intelligence
Utility gridHigh-voltage intake→
Protected powerSwitchgear + UPS→
AI computeCPU + GPU racks→
Model fabricFiber + switching→
Heat rejectionLiquid loop + plant
Real systems, representative configuration
Technical reference ↗The architecture follows publicly documented modern AI facilities: accelerator racks, CPU and storage hosts, high-speed fabric, redundant power, and direct-to-chip liquid cooling. Scene readings are clearly simulated and do not represent one named campus.