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There is no universal “AI cooling” or “AI power” design. The right combination depends on rack density, server design, coolant temperatures, climate, water availability and treatment, retrofit constraints, reliability targets, and the utility connection.
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Why AI changes the data-center infrastructure problem
Traditional enterprise racks often spread computing power across many cabinets. AI training and inference clusters can place large numbers of graphics processors, accelerators, memory modules, and high-speed network devices in a much smaller area. Every watt consumed by that equipment ultimately becomes heat that the facility must remove.
The U.S. Department of Energy’s 2024 design guide documents high-performance-computing examples above 125 kW per compute rack, compared with 60 kW racks observed in 2013. That figure is a documented example of how far rack density can rise, not a specification for every AI rack. Actual deployments vary by server generation, accelerator count, workload, and vendor configuration.
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Higher density changes several engineering limits at once:
- Heat transfer: room air may not carry enough heat away from tightly packed components without excessive airflow, fan power, or very low supply temperatures.
- Space: pumps, coolant-distribution units, heat exchangers, pipes, manifolds, and water-treatment equipment need space beyond the IT racks.
- Electrical distribution: a row or rack can require much more current, making busways, breakers, transformers, cabling, and protection settings more consequential.
- Reliability: a failure in a cooling loop or power path can affect a large amount of compute capacity concentrated in one location.
- Utility planning: a large AI campus can become a major, steady electricity customer whose connection affects generation, transmission, substations, tariffs, and resource-adequacy planning.
Why do AI data centers need liquid cooling?
Liquid can carry heat more effectively near the source than room air, allowing a cooling system to capture heat at the processor or server instead of first warming the entire room. This is why direct liquid cooling is increasingly considered for high-density AI and high-performance-computing equipment.
Liquid cooling is not automatically better for every facility. It introduces pumps, valves, heat exchangers, leak detection, coolant management, maintenance procedures, and compatibility requirements. A site must evaluate the complete system rather than treating a cold plate or immersion tank as a stand-alone solution.
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- Heat is captured at the IT equipment. In a cold-plate design, a liquid-cooled plate contacts the processor package or another hot component. In immersion cooling, equipment is placed in a fluid that absorbs heat directly.
- A recirculating IT loop carries the heat. Pumps move coolant through the servers or tanks and back toward a coolant distribution unit (CDU).
- The CDU transfers heat between loops. The CDU separates and controls the IT-side loop while transferring heat to a facility-side water or heat-rejection loop through a heat exchanger.
- The facility loop rejects heat. Condenser-water equipment, dry coolers, cooling towers, chillers, or other heat-rejection systems release the heat outdoors. The liquid loop therefore reduces the burden on room air; it does not eliminate the facility cooling plant.
- Residual heat is handled separately. Memory, storage, power supplies, networking equipment, lighting, and people still add heat. Many liquid-cooled halls retain air cooling for these loads and for parts of the IT equipment that are not liquid-cooled.
The Department of Energy describes this path as heat moving from IT equipment to a recirculating loop, through a CDU, and onward to a facility heat-rejection loop. A liquid-cooled hall can therefore still contain air handlers, fans, and other conventional equipment.
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Cold plates and immersion systems
Cold-plate systems attach a thermal plate to selected components while leaving the rest of the server in a conventional chassis. They can fit into rack-based operations but require compatible server designs, manifolds, connectors, pumps, and service procedures.
Immersion systems place servers in a nonconductive fluid. They can capture heat from more of the hardware, but they change how technicians install, inspect, remove, and repair equipment. Fluid handling, tank layout, filtration, and component compatibility become central design issues.
What are ASHRAE water classes?
ASHRAE water classes describe server supply-temperature ranges and help coordinate IT equipment with the facility loop. The DOE guide lists W17, W27, W32, W40, W45, and W+. The class is not a universal coolant recipe: server requirements, allowable temperatures, water chemistry, materials, controls, and heat-rejection equipment must all match. Equipment designed for one class should not be assumed to operate safely on another without confirmation from the manufacturer and the facility engineer.
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| Design question | Air cooling | Direct liquid cooling |
|---|---|---|
| Where heat is captured | Heat enters room air before air handlers move it to cooling equipment. | Heat is captured close to processors or other IT components and carried in a liquid loop. |
| High-density capability | Can support conventional loads; airflow, fan power, and supply-temperature limits become restrictive as rack density rises. | Designed for higher heat flux and documented high-density computing examples, including racks above 125 kW in the DOE guide. |
| Facility equipment | Air handlers, fans, chillers, dry coolers, or cooling towers sized for the room load. | CDUs, pumps, heat exchangers, piping, controls, and heat-rejection equipment, often alongside residual air cooling. |
| Retrofit impact | Uses familiar distribution and service practices when the existing plant has capacity. | May require structural, piping, electrical, controls, floor-space, and maintenance changes. |
| Temperature compatibility | Specified by the air-cooled server and room environmental limits. | Must match the server’s liquid-cooling design, ASHRAE water class, coolant chemistry, and facility-loop conditions. |
| Water considerations | Can use air-side or water-side heat rejection, depending on the plant. | May reduce room-air cooling demand but can still consume or require treated water in the heat-rejection plant. |
| Operational complexity | Familiar service model, with airflow balancing and filter, fan, and chiller maintenance. | Adds pumps, valves, leak detection, fluid quality, quick-disconnects, and procedures for servicing liquid-connected equipment. |
Neither approach wins on every criterion. A mixed design is common: liquid removes the concentrated processor heat while air handles residual loads and general room conditions.
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How rack density affects cooling design
Rack density is the amount of IT power installed in a rack, usually expressed in kilowatts. As density rises, the facility must move the same electrical energy out as heat through a smaller physical area. The result is a shift from room-level cooling assumptions toward component-, server-, rack-, and row-level heat capture.
At the chip and server level
Accelerator packages can create localized hot spots. Thermal interfaces, cold-plate pressure, coolant flow, allowable inlet temperature, and firmware controls affect whether the hardware can sustain its rated performance. A server may also contain air-cooled memory, storage, fans, and power-conversion components even when its processors use liquid.
At the rack and row level
Manifolds and quick-disconnects must deliver the required flow without creating unacceptable pressure drop. Rack layouts need clearance for service, hose routing, leak sensors, and isolation valves. Electrical and cooling paths should be coordinated so that a failed rack, CDU, pump, or breaker can be isolated without unnecessarily taking down adjacent capacity.
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At the hall and plant level
The heat-rejection plant must be sized for simultaneous load, outdoor conditions, redundancy, and future expansion. Operators should model peak and part-load behavior rather than sizing only for an average workload. Residual air loads, humidification, lighting, and power losses remain part of the facility heat balance.
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Cooling energy, water, and PUE
The Department of Energy states that “Cooling systems, which dominate facility infrastructure energy use, are also evolving rapidly to meet the increasing power densities of new AI systems.” Cooling choices affect both energy and water, but they do not optimize those resources in the same way under every climate or operating strategy.
What PUE measures
Power usage effectiveness (PUE) is the ratio of total facility energy to IT-equipment energy. A lower value means less overhead relative to the computing load. DOE’s 2025 update estimates an average national PUE of 1.145 in 2024 for facilities serving AI equipment and models 1.136 in 2030. The 2030 number is a projection, not a measured result.
PUE does not measure water consumption, carbon intensity, or the efficiency of an individual AI computation. A facility can improve PUE while using more water, or reduce water use with equipment that consumes more electricity. Operators need separate energy, water, and emissions metrics.
Why water treatment matters
Water-side systems may need filtration, corrosion control, biocide management, or reverse-osmosis treatment. DOE cautions that reverse osmosis can increase energy use and operating costs. Water availability, discharge rules, drought risk, makeup-water quality, and treatment chemicals should be evaluated with the same care as chiller capacity.
Why do AI data centers use so much power?
AI facilities consume power in three layers: the compute devices themselves, the networking and storage that feed them, and the cooling and electrical infrastructure that supports them. Training clusters can run many accelerators continuously, while inference sites may require high availability and rapid scaling. Dense racks also increase losses in transformers, power supplies, distribution conductors, pumps, fans, and heat-rejection equipment.
DOE’s December 2024 summary of the 2024 Lawrence Berkeley National Laboratory report estimates that all U.S. data centers consumed 4.4% of national electricity in 2023. The same summary projects a range of 6.7% to 12% in 2028. These figures cover U.S. data centers broadly, not AI workloads alone, and the 2028 range is a forecast rather than a measured outcome.
How power infrastructure changes for AI facilities
Power planning begins outside the building. Utilities and regulators must assess connection size, substation and transmission upgrades, resource adequacy, system costs, investment risk, and how a large customer’s load profile affects rates. DOE’s large-load brief treats these as utility-planning issues, not merely equipment purchases.
The electrical path inside the facility
- Utility interconnection: the site receives a service sized for present load, planned expansion, fault levels, and required redundancy.
- Medium-voltage transformation: transformers step voltage to the levels used by switchgear and distribution equipment.
- Switchgear and protection: breakers, relays, grounding, arc-flash controls, and selective coordination protect people and equipment.
- Facility distribution: busways, feeders, UPS systems, batteries, generators, and automatic-transfer equipment deliver power through the data hall.
- Rack conversion: rack-level power shelves or power-distribution units convert and distribute energy to servers, with connectors and breakers rated for the current.
- Monitoring and controls: metering tracks branch loads, temperature, power quality, alarms, and remaining capacity so operators can avoid overloads.
As rack power rises, row-level and rack-level choices become more consequential. A distribution system that works for a conventional rack may lack the conductor capacity, connector ratings, fault protection, or service clearance required by a high-density AI rack.
What is NVIDIA’s 800 VDC proposal?
In a May 2025 technical blog, NVIDIA proposed converting grid-side AC to 800 VDC at the data-center perimeter and distributing DC toward future AI racks. The company said the architecture is intended to support 1 MW IT racks starting in 2027. Those are vendor roadmap claims, not proof of a universal standard or independently verified deployment timetable.
An 800 VDC design would change conversion points, distribution conductors, protection, connectors, maintenance procedures, and equipment compatibility. A facility considering it would need evidence from its server, power-supply, switchgear, safety, and utility partners. Existing AC distribution may remain the practical choice where equipment availability, standards, service capability, and retrofit cost favor it.
A practical design framework
Operators can evaluate a proposed AI hall by answering these questions in order:
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- What is the actual rack envelope? Record continuous, peak, and future rack power rather than using a generic “AI rack” label.
- Which components are liquid-cooled? Identify processors, memory, networking, storage, and power electronics that remain air-cooled.
- Which water class and coolant conditions apply? Confirm supply-temperature range, chemistry, materials, pressure, flow, and warranty requirements.
- Where is heat exchanged? Map the IT loop, CDU, facility loop, chillers or dry coolers, cooling towers, and emergency modes.
- What happens during failure? Test loss of a pump, CDU, chiller, cooling tower cell, power feeder, UPS module, or utility source.
- What are the water and energy boundaries? Measure PUE separately from water withdrawal, consumption, treatment energy, and discharge.
- Can the building support the retrofit? Check floor loading, pipe routes, drainage, leak containment, electrical rooms, generator capacity, and maintenance access.
- What is the utility timeline? Align construction with interconnection studies, substation work, transformer lead times, permits, and tariff decisions.
Common failure modes and how to avoid them
- Assuming liquid cooling removes all air equipment: retain an air-cooling plan for residual loads and non-liquid components.
- Treating 125 kW as a universal rack rating: use the DOE figure as historical context and size from the actual server configuration.
- Mixing incompatible loops: verify water class, coolant chemistry, pressure, materials, and temperature at every interface.
- Optimizing PUE alone: track water treatment, water consumption, emissions, and compute efficiency separately.
- Designing only for average load: include workload spikes, hot outdoor conditions, simultaneous failures, and expansion capacity.
- Copying a vendor roadmap: classify proposed architectures such as 800 VDC by maturity, available equipment, independent demonstrations, and service support.
- Ignoring maintenance: provide isolation valves, drains, leak detection, spare pumps, safe electrical clearances, and procedures that technicians can execute without exposing live equipment to fluid or arc-flash hazards.
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