Cooling Technologies
Cooling is now the binding constraint on AI compute density. As GPU power consumption has increased from 300W (A100) to 700W (H100) to 1000W+ per chip (B200), the ability to remove heat has become the limiting factor in how many GPUs you can pack into a given space. The cooling technology frontier is moving faster than it has in decades.
Air Cooling - Still Common, Running Out of Headroom
Traditional data centers use air cooling: cold air flows from raised floor tiles through server racks, picks up heat, and returns as hot air to be chilled by CRAC (Computer Room Air Conditioning) units:
Cold aisle / Hot aisle containment: ββββββββββββββββββββββββββββββββββββββββ β HOT AISLE (hot exhaust from servers) β ββββββββββββββββββββββββββββββββββββββββ€ β SERVER RACK (frontβback airflow) β ββββββββββββββββββββββββββββββββββββββββ€ β COLD AISLE (cold supply air) β ββββββββββββββββββββββββββββββββββββββββ Limitations: Air has very low thermal capacity (heat absorption) Effective for: up to ~25 kW/rack Usable for AI: small inference servers, CPU-based ML Not viable for: modern H100/B200 GPU racks
Air cooling is cheap and proven, but maxes out around 25 kW/rack. An 8Γ H100 DGX server needs 10 kW and already pushes air cooling near its limits. An NVIDIA GB200 NVL72 rack at 120+ kW is impossible to air-cool.
Direct Liquid Cooling (DLC)
DLC routes chilled water directly to cold plates mounted on GPUs and CPUs. The liquid absorbs heat far more efficiently than air (water has ~3,500Γ the heat capacity of air by volume):
- Cold plates mounted directly on GPU die or heat spreader
- Chilled water (typically 25β45Β°C supply) circulates through the plates
- Rear-door heat exchangers or in-row cooling units reject heat from the water loop to the building chiller
- Handles 40β100 kW/rack reliably
- NVIDIA DGX H100 and H200 systems ship DLC-ready
- Does not eliminate air cooling entirely - some components (memory, power supplies, motherboard) still need air
Immersion Cooling
The most capable cooling technology: submerge entire servers in dielectric fluid (a non-conductive liquid that doesn't damage electronics). The fluid absorbs heat and carries it to a heat exchanger:
| Type | How It Works | Notes |
|---|---|---|
| Single-phase | Servers in mineral oil or synthetic fluid; fluid stays liquid; pumped to heat exchanger | ~150 kW/tank; used by some HPC and crypto operators; slower to service |
| Two-phase | Fluid boils off heat (phase change) and recondenses; much higher heat transfer rate | ~250 kW/tank; most efficient; 3M Novec (now discontinued) was primary fluid; alternatives emerging |
Immersion cooling can handle 250+ kW/tank and requires no air cooling at all. Advantages: complete silence (no fans), higher component reliability (no vibration, no humidity variation), smaller facility footprint. The challenge: servicing servers requires removing them from the fluid tank, which is messy and slower than air-cooled rack service.
Rear-Door Heat Exchangers
A compromise between air and full liquid cooling: a door-sized heat exchanger mounts on the back of a standard server rack. Chilled water runs through the door; air from the servers passes through it and is cooled before re-entering the room. Handles 30β50 kW/rack with no rack modification. Used as an upgrade path for existing air-cooled data centers.
NVIDIA's GB200 Cooling Requirements
The NVIDIA GB200 NVL72 "rack" (72 GPUs + 36 Grace CPUs in a single rack system) illustrates where the industry is heading:
- 120β140 kW total rack power
- Requires liquid cooling - NVIDIA ships the system with integrated liquid cooling; no air-cooled variant
- Copper manifold runs to each GPU; factory-integrated coolant distribution unit (CDU)
- Data centers must have liquid cooling infrastructure in place before GB200 clusters can be deployed
- This requirement has delayed many GB200 deployments as operators retrofit facilities
Industry Trends
- All major AI hardware vendors (NVIDIA, AMD, Intel) are designing future chips that assume liquid cooling - not just support it optionally
- New AI data centers being built in 2025β2027 are designed from the ground up for liquid cooling infrastructure
- Existing colocation facilities are rapidly losing relevance for AI training workloads - they cannot support the density
- Cooling infrastructure lead time (12β18 months for a new liquid-cooled facility) is now a competitive advantage for cloud providers who built early