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NVIDIA is reshaping AI infrastructure from Blackwell to Rubin, shifting its focus from standalone GPUs to standardized full-stack AI Factory rack-scale systems covering power, networking and thermal management. Liquid cooling has become a core prerequisite for scalable AI cluster delivery, rather than a marginal accessory for AI data center cooling.

The Middle East data center market sees explosive growth, with a CAGR of 23.91% projected from 2024 to 2030 and market size to exceed $6.98 billion by 2030. Driven by the UAE and Saudi Arabia, the region has invested over $300 billion in AI infrastructure. Large-scale AI parks and computing clusters generate strong demand for professional AI data center cooling solutions.

The liquid cooling industry adopts two mainstream pipeline solutions: mature stainless steel and innovative polymer pipelines. As key parts of the complete data center liquid cooling system, they cater to diverse construction needs and support the upgrading of high-density AI computing cooling infrastructure.

Many operators regard CDU merely as a simple heat exchange cabinet without understanding its internal components and respective functions. This article disassembles a complete CDU unit and elaborates on six core functional modules with detailed design rationale, supporting stable operation of CDU liquid cooling systems.

Official statistics from China’s MIIT outline the overall PUE landscape of domestic data centers. In 2023, large-scale data centers posted an average PUE of around 1.35, while hyperscale facilities averaged 1.27. Yet average figures obscure huge gaps between new and legacy sites. New AIDC projects equipped with cooling tech hit PUE 1.1–1.2, whereas outdated stock facilities stay at 1.4–1.8, making aggregate averages less indicative of real technical capacity. Global hyperscalers like Google and Microsoft maintain steady PUE 1.1–1.2, with sites adopting free cooling or immersion cooling reaching 1.05–1.08, fully demonstrating the core advantages of data center liquid cooling PUE.

Most operators focus on pipeline layout, CDU deployment and power capacity expansion when launching liquid cooling upgrades for old data halls, while ignoring the fundamental prerequisite: floor structural load bearing capacity. Any miscalculation on load bearing will render all subsequent renovation plans unworkable, a critical reminder delivered by professional data center liquid cooling supplier for all transformation projects.

Many liquid cooling projects face typical dilemma when choosing between centralized and distributed CDU architectures. Teams often regret their selection after commissioning: centralized CDU delivers unified management but triggers large-area outages once a single unit fails; distributed CDU improves granular reliability yet disperses maintenance points and increases daily operation workload. In fact, neither architecture is universally superior — each fits clear and non-overlapping scenarios for modern data center liquid cooling system deployment.

As AI computing density continues rising, rack power loads have grown from 10kW–20kW to 50kW–100kW. Traditional air cooling can no longer support high-load AI servers, causing thermal throttling and performance degradation. As a key part of the complete data center liquid cooling system, liquid cooling has become the standard upgrade for high-density computing rooms. However, full liquid cooling features high costs and long construction cycles, making it unfriendly for legacy facility upgrades. Air-liquid CDU and liquid-liquid CDU have become two core technical routes for modern AI data center cooling transformation.

Liquid cooling systems cover immersion, cold plate and spray types, consisting of cold source equipment, cooling media, piping, monitoring and auxiliary components. The booming high-density computing demand promotes continuous optimization of the complete data center liquid cooling system, which underpins the stable operation of modern intelligent computing data centers.

Following Morgan Stanley, Bernstein has released an in-depth analysis of NVIDIA’s Rubin platform, highlighting a dramatic surge in rack-level thermal system value rather than GPU performance alone. Data shows the liquid cooling value per rack rises from $51,000 on GB200 to $158,000 on Rubin, a 210% increase of 3.1 times, marking a revolutionary upgrade of liquid cooling for AI GPU data center infrastructure.