Against the backdrop of rapidly growing AI computing power, Singapore enterprises are reassessing a critical question: what should they look for when selecting an AI data center solution? HUAWEI Digital Power’s AI data center infrastructure offering points out that enterprises should focus on three key categories of metrics: reliability, deployment speed, and energy efficiency.
As one of the largest data center hubs in the Asia‑Pacific region, Singapore carries about 60 percent of the world’s submarine cable traffic. However, the realities of high electricity tariffs, limited land resources, and dense urban construction mean that AI data center selection is no longer just a technical issue – it is an integrated challenge of resources and costs.
AI Data Centers: Definition and Evaluation Framework
An AI data center solution refers to an infrastructure package tailored for large-scale model training and inference, covering power supply, cooling, backup power, and modular delivery—all of which are essential.
The selection criteria have also evolved. It is no longer just about capacity, but about three core capabilities:
Can it support high-density GPU workloads?
Can it ensure long-term stable operation?
Can it be deployed quickly and scaled flexibly?
HUAWEI Digital Power, based on its RAS framework (Reliability, Agility, Sustainability), integrates these capabilities into a unified evaluation system.
Core Architecture: Power Supply, Cooling, and Modularization
For power supply, the HUAWEI PowerPOD prefabricated power module achieves a prefabrication rate of up to 90 percent, reducing the delivery cycle from 28 weeks to 18 weeks. On the cooling side, in high-density AI computing environments, liquid cooling has become a critical path. The TMU, as a liquid cooling control unit, provides real‑time monitoring of pressure, water quality, and conductivity, and supports a fast recovery mechanism within 20 seconds, upgrading the system from “passive cooling” to “active control”. For backup power, the HUAWEI UPS5000‑H delivers excellent system efficiency and can meet the power stability requirements under high‑load fluctuation scenarios. The overall solution adopts a factory‑prefabricated and on‑site rapid assembly modular delivery model, which effectively saves floor space and is well‑suited to Singapore’s urban space constraints.
Challenges Facing Singapore and Successful Practices in Malaysia
These challenges are not unique to Singapore. In Johor, Malaysia, a landmark AI data center project delivered a surprising result – it completed the construction of a 60 MW high‑density data center in just 11 months. Traditionally, a data center of similar scale would take more than 24 months. Moreover, Johor’s year‑round high temperature, high humidity, and water resource constraints made the challenge even more severe. HUAWEI Digital Power adopted a fully prefabricated modular solution – nearly a thousand “Lego‑like” prefabricated modules were produced in the factory, synchronised with on‑site civil construction, and quickly assembled upon arrival. The power system used a distributed architecture – “one container, one power path” – with modules decoupled from each other, so that a failure in one module does not affect the operation of others.
The result: delivery time was cut by 50 percent, PUE was controlled below 1.4, and per‑rack power density exceeded 20 kW. This project won the DCD “Editor’s Choice Data Center Project of the Year” award. HUAWEI Digital Power also received two awards at the 2025 W.Media Asia‑Pacific Cloud & Data Centre Awards – “Sustainable Design & Construction” and “Energy Optimisation Innovation” – for its PowerPOD and TMU solutions.
Trends and Conclusions: The Selection Logic Is Being Reshaped
Looking ahead, the criteria for AI data center selection are shifting: from “device performance first” to “system reliability first”, from “point optimisation” to “coordinated optimisation of power and cooling”, and from “manual operations” to “predictive and automated operations”. In dense urban markets like Singapore, this trend will continue to accelerate.
For enterprises, the key to selection may not be any single metric, but finding the right balance among reliability, deployment speed, and energy efficiency that best fits their business rhythm.
Frequently Asked Questions (FAQs)
Q1: What is the most important metric when choosing an AI data center solution?
Reliability, energy efficiency, and deployment speed are the three core indicators.
Q2: Why is the selection of AI data centers more stringent in Singapore?
Due to higher electricity tariffs, limited land, and the dense urban structure, there are greater demands on energy efficiency and space utilisation.
Q3: What role does the thermal management control unit（TMU） play in the selection process?
The thermal management control unit enhances the stability of the liquid cooling system, making it suitable for high‑density AI training environments.
Conclusion
As Singapore serves as the Asia‑Pacific data center hub, the logic of data center selection is being redefined under the dual pressure of surging AI computing demand and local resource constraints. The Grid-interactive AIDC solution proposed by HUAWEI Digital Power aims to develop a reliable,energy-efficiency,fast-delivery,and grid-friendly AIDC solution that maximizes tokens per watt.
The successful practice of the Johor project in Malaysia demonstrates that a fully modular prefabricated approach can effectively cope with harsh environmental challenges such as high temperature, high humidity, and water scarcity, achieving both shortened delivery cycles and controlled PUE. For enterprises, AI data center selection is no longer a procurement issue, but a systemic decision that requires comprehensive consideration of reliability, deployment speed, energy efficiency, and long‑term operational costs.
