How is AI changing the way data centres cool?
The rise of AI technologies in recent years has fundamentally transformed the way data centres operate. Traditional server tasks are increasingly being replaced by computationally intensive machine learning models, neural networks and real-time data analytics. These systems result in significantly more intensive heat generation, posing significant challenges for precision cooling equipment and its designers and operators.
Modern data centres are no longer just CPUs, but are also seeing an increasing proportion of graphics processing units (GPUs) and other dedicated AI accelerators such as TPUs and NPUs. These high-performance chips perform thousands of parallel operations per second, generating extremely high heat. A GPU rack, for example, can generate several times more heat than a traditional server. In addition, heat is often concentrated in a specific zone, increasing the risk of local overheating.
It is not only centralised data centres that need to rethink their cooling strategy, but also the ever-expanding edge AI infrastructures that are emerging in industrial machines, self-driving vehicles or smart city systems. These systems often operate in very confined spaces in varying environmental conditions where it is not possible to accommodate conventional large cooling units. In such environments, fast and efficient heat dissipation is particularly important, even in extreme conditions such as dusty, hot or humid air. This requires completely new, compact, modular and energy-efficient cooling solutions.
The rise of AI therefore requires not only greater cooling
performance, but also a change of approach in the design and operation of
cooling systems. The key to the solution is to combine precision cooling with
intelligent control. Adaptive airflow control, supported by sensors, allows
real-time temperature monitoring to automatically adjust airflow direction and
intensity. Zoned cooling means that the entire data centre does not need to be
cooled, but only those areas where the heat load is particularly high. In
addition, liquid cooling systems are gaining ground as an efficient alternative
to traditional air-jet technologies.
With the heat loads generated by artificial intelligence,
cooling is no longer just a support function but a mission-critical element.
Outdated, undersized or non-scalable systems pose serious risks: they can lead
to performance degradation, hardware damage, downtime and loss of energy
efficiency (PUE).
Our company offers up-to-date solutions for the design,
implementation and maintenance of precision cooling systems that are
specifically optimised for AI workloads – whether in a large data centre or an
industrial edge AI solution.