Fan Wall for Large-scale AI Training/inference Data Centers with Dense GPU Rows

Large-scale fan wall (air wall) is a centralized near-aisle precision cooling solution engineered exclusively for massive AI compute facilities loaded with dense GPU racks.

It replaces scattered traditional CRAC/CRAH and scattered in-row coolers, deploying full-height modular fan wall assemblies at aisle terminals to horizontally supply uniform cold air for entire GPU rows. It addresses core pain points of high heat load, GPU thermal throttling, high cooling power consumption and difficult capacity expansion in AI training/inference clusters (50–500+ racks).

Core Structural Composition

- High-static-pressure IE5 EC fan matrix (redundant fan design for no single point of failure)

- Large-area chilled water cooling coils (18/26°C standard chilled water loop, optional dual DX + chilled water dual-source coils)

- Integrated air mixing & flow equalization baffles to eliminate local hotspots along long rack rows

- Intelligent variable-flow water control valves + BMS integrated temperature monitoring sensors

- Sealed cabinet frame matching full rack height for aisle containment matching

Working Flow Optimized for Dense GPU Rows

1. Hot air recovery: Capture high-temperature exhaust air (42–56°C) discharged densely from GPU rack rear hot aisles

2. Centralized heat removal: Mass coil surface quickly extracts massive heat from concentrated GPU waste heat

3. Long-distance uniform air delivery: EC fan array pushes stabilized cold air (24–29°C) horizontally 15–30 meters to cover full GPU rows

4. Dynamic load matching: BMS links real-time GPU inlet temperature data to adjust fan RPM and chilled water flow. During AI training peak loads, fan power rises automatically; under low inference idle loads, it drops sharply to save energy.

5. Full containment coordination: Paired with hot/cold aisle closed baffles to block cold-hot air mixing, cold air utilization rate exceeds 92%.

Typical Application Scenarios

1. Large AI training base with 100–500 dense GPU racks, long continuous hot/cold aisles

2. Mass inference data centers running stable 24/7 large model reasoning tasks

3. New-build supercomputing AI parks pursuing low PUE and low long-term operating cost

4. Facility renovation projects upgrading old low-density server rooms to high-density GPU compute zones