Business

Powering the Future: How AI and LLMs in Asia are Revolutionising Data Centre Efficiency

AI and LLM growth in Asia impact data centre energy consumption.

Published

on

TL;DR:

  • AI and Large Language Models (LLMs) are driving increased energy consumption in data centres, with estimates suggesting a potential doubling of global electricity consumption between 2022 and 2026.
  • Singapore’s National Multimodal LLM Programme (NMLP) aims to develop a base model accounting for Southeast Asia’s multilingual environment, potentially increasing data centre energy consumption in the region.
  • Advanced cooling systems like Huawei’s FusionCol8000-C and power supply solutions like FusionPower6000 3.0 are helping to improve data centre energy efficiency and sustainability.

The Rise of AI and Large Language Models in Asia

Artificial Intelligence (AI) and Large Language Models (LLMs) have led to a surge in energy consumption in the computing world. Since the introduction of ChatGPT in November 2022, several countries have announced plans to develop their own LLMs to support applications across various industries. One such initiative is Singapore’s National Multimodal LLM Programme (NMLP), launched by the Infocomm Media Development Authority (IMDA) and other research institutions. The NMLP aims to create a base model that accounts for Southeast Asia’s multilingual environment, supporting national-level strategies in AI and research and development.

The Energy Consumption Challenge

The growing adoption of generative AI and LLMs will lead to increased energy consumption in data centres in the coming years. Data centres are known to be significant energy users due to the high amounts of power needed to run and cool servers. The International Energy Agency (IEA) estimates that data centres and data transmission networks account for 1 to 1.5 per cent of global electricity use, respectively. The IEA also predicts that global electricity consumption from data centres, cryptocurrencies, and AI could double between 2022 and 2026.

Power Usage Effectiveness (PUE)

Power Usage Effectiveness (PUE) is a calculation of data centre energy efficiency first introduced in 2007. It has become the most significant metric for governments and organisations seeking to monitor energy use trends and maximise operational efficiency.

Optimised Cooling with Chilled Water

Data centre cooling systems play a crucial role in maximising operational efficiency and reducing energy consumption. One such solution is the in-room horizontal airflow chilled-water cooling system for medium and large data centres, like Huawei’s FusionCol8000-C. This system supports higher water temperatures without the need for a raised floor, reducing power consumption and overall energy consumption of the chilled water system by more than 20 per cent.

Uninterrupted Power with a Lower Footprint

Data centres must deliver exceptional performance with high levels of reliability and availability for their customers while remaining sustainable. Traditional power supply systems in large data centres often involve complex devices from different manufacturers, presenting challenges such as intricate installation and elevated safety risks. Prefabricated solutions like Huawei’s FusionPower6000 3.0 provide uninterrupted power for data centres while minimising the footprint of power supply and distribution systems.

Advertisement

Improving Sustainability for Data Centres

As AI and LLM developments demand ever-greater computing power and increase energy consumption, governments worldwide are looking at improving data centre sustainability. Working with solution partners like Huawei, which has a track record of developing sustainable data centre solutions, can help achieve innovation goals while staying on track for climate targets.

Comment and Share

What steps do you think governments and organisations should take to ensure the sustainable growth of AI and LLMs in Asia? Share your thoughts below and don’t forget to subscribe for updates on AI and AGI developments.

You may also like:

Trending

Exit mobile version