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Latest energy efficiency publications


Magnetic circuits could radically reduce AI energy consumption

The combination of AI and large data sets has profoundly improved our ability to model the world around us, predict its next move and recognize its images and patterns.

Underpinning all of this data-driven innovation, though, are servers and accelerators that can devour astronomical amounts of energy, depending on the task.

Last year, research indicated that training a single AI algorithm can require up to 284 tonnes of carbon dioxide – five times the lifetime emissions of an average car.


Adopting a low energy and low water consumption approach

Excool is specialists in indirect evaporative cooling . Over the last decade the data centre world has changed, the demand from the market is very different now in 2020 compared to 2010 and data centres began to implement IEC into their builds. 2010 was about low energy and resultant low PUE. But generally the sites were not so large and 5MW site was considered a large site, so high-water use was not a consideration.


Data centres aren’t using as much energy as we thought

Researchers have criticised what they call the “conventional wisdom” that data centre energy utilisation is spiralling out of control, claiming such narratives ignore the great gains made in data centre efficiency.

Revised global data centre energy use estimates were published last week in the journal Science by researchers seeking to clarify the environmental impact of the server farms that underpin the cloud and much of our digital world.


#DCWSG19: Energy efficient cooling at no extra cost

Energy-efficient cooling at no extra cost? It’s not too good to be true. At #DCWSG19, Peter Thomsen, Director of Building System Solutions at Armstrong Fluid Technology, explains why Armstrong’s intelligent cooling solutions are an investment – not at expense. Learn More: https://bit.ly/2qFUnyj


How Verizon deploys machine learning to improve energy efficiency

Over the past few decades, technological advances have enabled telecom service providers to consolidate their network infrastructure. The reduction in equipment size, coupled with an improved ability to bridge larger distances, has also allowed service providers to reduce their data centre footprint.

But with the reduction in data centre sites, the modern facility has also become comparatively supersized and energy hungry, mainly due to the never-ending increase of network traffic. To mitigate this challenge, companies such as Verizon are turning to machine learning and data analytics to improve the energy efficiency of facilities.