AI Infrastructure Challenges: Scaling with Liquid Cooling

As industries increasingly turn to artificial intelligence (AI) to gain a competitive edge, scaling AI infrastructure to support evolving technology becomes a critical factor. AI-powered systems, such as those used in high-frequency trading (HFT) and autonomous systems, require massive computational power. As AI hardware becomes more powerful, it generates more heat, necessitating innovative cooling solutions to keep systems running smoothly.

How can an AI-driven trading firm leverage liquid cooling to meet its scaling needs, ensuring optimal performance, energy efficiency, and cost predictability? T5 Data Centers determined how with the proper infrastructure that is enhancing the way AI-powered businesses scale.

Growing High-Performance AI Infrastructure

For a leading Chicago-based quantitative trading firm, scaling AI infrastructure wasn’t just about adding more hardware — it was about ensuring that hardware could run efficiently without overheating or running into power bottlenecks. The firm relied on high-density GPU (Graphics Processing Unit) clusters to run its trading algorithms. These systems require up to hundreds of watts per square foot of power density, which can overwhelm traditional cooling systems. As the firm looked to expand, it realized its existing infrastructure couldn’t handle the load.

The firm, after grappling with extreme energy price fluctuations and disruptions at their previous facility, was in dire need of a solution that could accommodate growing power and cooling requirements while also offering predictable costs. They found their answer in T5 Data Centers, which provided a scalable, liquid-cooled data center solution.

Liquid Cooling for Optimal Scalability

The solution that T5 Data Centers designed was a liquid-cooled data center in Charlotte, North Carolina. In simple terms, liquid cooling is a method of cooling computer components by transferring heat away from them using a liquid coolant. The data center was retrofitted to handle power densities of up to 700 watts per square foot, allowing it to support the firm’s dense GPU clusters. Liquid cooling provided a more efficient way to remove heat directly from the server racks, reducing energy consumption and ensuring a more stable operating environment.

Beyond cooling, the data center design also included redundancy for over 13 MW of power capacity — ensuring that the trading firm could continue to scale its operations without encountering power shortages or interruptions. This solution not only met the firm’s immediate needs but also set the stage for future growth as AI systems continue to become more powerful.

Future-Proofing AI Operations

As AI technology advances, the need for scalable, efficient infrastructure will continue to grow. Liquid cooling offers a sustainable solution to the power and cooling challenges of AI, allowing companies to support more powerful AI hardware while maintaining energy efficiency. The success study of this trading firm illustrates how the proper infrastructure can provide a platform for future growth, ensuring that businesses are equipped to keep up with the pace of technological change.

–

To dive deeper into the specifics of how liquid cooling and scalable infrastructure helped this trading firm meet its AI needs, download the full case study.