Scale-up Strategies: The Crucial Impact of Cooling Methods on AI Performance Success
In the rapidly evolving world of artificial intelligence (AI), one aspect that is gaining significant attention is the cooling infrastructure. As AI infrastructure spending is forecasted to reach an impressive $90 billion by 2028, the need for efficient and sustainable cooling solutions has become more crucial than ever.
Traditional cooling systems, which consume up to 40% of data center power, are no longer sufficient to meet the thermal demands of modern AI workloads. The latest AI processors generate up to 1,200W per chip, and this number is only increasing. Today's AI servers consume 10-12kW each, with racks exceeding 100kW. To address this challenge, organizations are turning to advanced cooling technologies that can directly support both operational efficiency and environmental sustainability goals.
The thermal challenge is driving the mandatory adoption of liquid cooling solutions. These solutions, such as direct-to-chip liquid cooling (DLC), rear door heat exchangers (RDHX), and immersion cooling, are becoming increasingly popular. DLC, for instance, has become a mainstream production technology for high-density AI workloads, cooling the processor directly via liquid coolant, and managing over 125 kW per rack today. Google’s Project Deschutes, featuring a 1 MW rack design enabled by DLC, exemplifies this trend, allowing unprecedented compute density.
RDHX, on the other hand, combine liquid cooling with cold air, typically used in space-constrained data centers with rack densities of 40-60 kW. They serve as a retrofit solution and a hybrid approach where about 70% liquid cooling and 30% air cooling is used. Immerersion cooling is an emerging technology where servers are submerged in dielectric fluids. It can handle power densities above 150 kW per rack and is seeing adoption primarily in AI-specific data centers and crypto-mining applications.
Fujitsu's two-phase boiling cooling technology enhances closed-loop liquid cooling by boiling the coolant and using latent heat for superior heat dissipation, doubling cooling performance compared to traditional single-phase closed-loop cooling. This technology provides improved environmental impact and safety and has been mass-produced since 2017, with ongoing enhancements to address GPU heat loads in 2025-era AI data centers.
As the AI market bifurcates between organizations that view cooling as a strategic imperative and those treating it as a tactical challenge, an integrated approach to cooling strategy enables faster deployment, more efficient resource utilization, and greater long-term scalability. Engaging with cooling technology providers early in the AI planning process ensures thermal strategies align with deployment timelines and business objectives.
In the AI era, the cooling infrastructure determines how quickly you can create value from your technology. Many organizations are discovering that their existing cooling infrastructure cannot support the thermal demands of modern AI workloads. The latest advancements emphasize higher cooling densities enabled by direct liquid contact with chips, hybrid liquid-air cooling at rack exhausts, two-phase cooling innovations, and growing interest in immersion cooling, all essential to sustainably support the rapid growth in AI computing power in data centers.
The industry outlook forecasts liquid cooling becoming essential, with many new data centers integrating these technologies from the design phase to cope with AI hardware’s increasing power and thermal demands, aiming to optimize site power efficiency and operational costs. The sustainability implications are important, as traditional cooling systems consume up to 40% of data center power. Organizations implementing advanced cooling solutions are achieving 20% more compute capacity from the same power envelope, creating a competitive edge in the AI race. Forward-thinking operators are designing for 250kW+ per rack and developing integrated approaches that optimize cooling, power distribution, and compute resources as a unified system.
In conclusion, the future of AI cooling is one of innovation and sustainability. The latest advancements are paving the way for more efficient, environmentally friendly, and scalable cooling solutions that will support the exponential growth of AI computing power in data centers.
Technology and data-and-cloud computing industries are positioning themselves for the future by investing in advanced cooling solutions, recognizing the critical role of cooling infrastructure in the success of artificial intelligence (AI) projects. These innovative cooling technologies, including direct-to-chip liquid cooling, hybrid liquid-air cooling, and immersion cooling, are essential for sustaining the rapid growth of AI computing power, promoting operational efficiency, and ensuring environmental sustainability. By adopting these technologies, organizations can achieve 20% more compute capacity from the same power envelope, gaining a competitive edge in the AI era.
