AI in-charge of Google’s data centres cooling

TRME datacentreEnergy consumption by data centres has become a pressing issue for the tech industry. (Image source: Scanraill/Adobe Stock)Google has given control of cooling several of its leviathan data centres to an artificial intelligence (AI) algorithm

The information and communication technology (ICT) sector including data centres generates up to two per cent of the global CO2 emissions, a number on par to the aviation sector contribution. Data centres are estimated to have the fastest growing carbon footprint from across the whole ICT sector, mainly due to technological advances such as the cloud computing and the rapid growth of the use of Internet services.

Over the past couple of years, Google has been testing an algorithm that learns how best to adjust cooling systems — fans, ventilation, and other equipment — in order to lower power consumption. This system previously made recommendations to data centre managers, who would decide whether or not to implement them, leading to energy savings of around 40 per cent in those cooling systems.

Now, Google says, it has effectively handed control to the algorithm, which is managing cooling at several of its data centres all by itself.

“It’s the first time that an autonomous industrial control system will be deployed at this scale, to the best of our knowledge,” says Mustafa Suleyman, head of applied AI at DeepMind, the London-based artificial-intelligence company Google acquired in 2014.

The project demonstrates the potential for AI to manage infrastructure — and shows how advanced AI systems can work in collaboration with humans. Although the algorithm runs independently, a person manages it and can intervene if it seems to be doing something too risky.

The algorithm exploits a technique known as reinforcement learning, which learns through trial and error. The same approach led to AlphaGo, the DeepMind programme which vanquished human players of the board game Go.

DeepMind fed its new algorithm information gathered from Google data centres and let it determine what cooling configurations would reduce energy consumption. The project could generate millions of dollars in energy savings and may help the company lower its carbon emissions, says Joe Kava, vice-president of data centres for Google.

Energy consumption by data centres has become a pressing issue for the tech industry. A 2016 report from researchers at the US Department of Energy’s Lawrence Berkeley National Laboratory found that US data centres consumed about 70bn kilowatt-hours in 2014 — about 1.8 per cent of total national electricity use.

But efforts to improve energy efficiency have been significant. The same report found that efficiency gains are almost cancelling out increases in energy use by new data centres, although the total is expected to reach around 73bn kilowatt-hours by 2020.

“Use of machine learning is an important development,” maintains Jonathan Koomey, one of the world’s leading experts on data centre energy usage. But he adds that cooling accounts for a relatively small amount of a centre’s energy use, around 10 per cent. Koomey thinks using machine learning to optimise the behaviour of the power-hungry computer chips inside data centres could prove even more significant.

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