What will AI mean to the traditional datacentre?
Business Process Automation

What will AI mean to the traditional datacentre?

The recent decision by US-Norwegian business Kolos to build a giant, 600,000m2 datacentre in the city of Ballangen, Norway, is on the surface at least, a wise decision. Ballangen, which incidentally is the birthplace of singer Frida from 70s pop group Abba, is inside the Arctic circle, which sort of solves the cooling issue. Maybe.

As demands to store and manage data accelerates, driven by increased machine connectivity and data analytics, so the pressure on traditional datacentres increases, certainly in terms of capacity and cooling. This Kolos site, chosen primarily for its clean, renewable energy, is expected to house 70MW of IT equipment, eventually scaling up to offer 1,000MW, within 10 years of construction.

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The quest for bigger and better is understandable but when does size become an issue? Surely we can’t keep building huge datacentres in the arctic to keep up with the insatiable demand for data? There is a school of thought that the demand for AI-enabled machines will alter the course of datacentre development. Machine learning is, after all, capacity and power hungry.

“A combination of deep machine learning and analytics on growing data sets is driving adoption of IT systems that are more similar to high-performance computing clusters,” says Daniel Bizo, a senior analyst for datacentre technologies at 451 Research. “Such systems are high-powered and require much more power and cooling capacity than the average rack. Many traditional facilities will be stretched to meet such requirements at cost.”

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Marc Ambasna-Jones

Marc Ambasna-Jones is a UK-based freelance writer and media consultant and has been writing about business and technology since 1989.

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