TRENDING
Greater data centre capacity requires increasing power, yet energy availability is shrinking. As more homes are built, more businesses come online and more people use AI and Gen AI, the power and data storage needs of both will grow.
This creates a square peg / round hole situation for both the tech industry, who are trying to meet customer expectations, and governments, who need to secure the energy supply for homes and businesses. How can both get what they need to satisfy these requirements?
Data centre demands: how and where is the power used?
Around 2 % of global energy generation is consumed by datacentres and transmission networks according to the IEA. In terms of specific workloads, McKinsey & Co are forecasting a 39 % CAGR increase in Generative AI workload demands and 16 % CAGR on other workloads for global data centre capacity demand by 2030. A recently announced hyperscaler data centre is almost the size of Manhattan. This puts pressure on national grids.
Within the data centre, power is used for compute, storage, networking and cooling. Historically, water cooling was widely used, but many operators have stopped and are now using more traditional chillers and cooling strategies, driven by electricity, which means less power is going to the compute load and it increases the power demand even further.
In terms of AI, the latest model of GPU represents the daily energy consumption of a“ standard” 4-person home at ~ 30kWh. GPU manufacturers are shipping hundreds of thousands of GPUs every quarter. This demand for AI is taking electricity away from other sources. Put simply, the industry is behind the curve of demand.
The demand vs consumption spiral
One might think the answer is to generate more power. However, it’ s not a simple calculation: adding more electricity doesn’ t necessarily mean more data centre capacity and keeping homes and businesses powered. For countries who are investing heavily in building data centres, the amount of
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