Power
Optimising power management in data centres amid surging AI and ML demands
By Phil Goff, product marketing manager – telecom, cloud & industrial / regional sales manager (UK & Ireland), Flex Power Modules
T
he relentless advance of AI, machine learning (ML), cryptocurrencies and cloud computing is dramatically reshaping data centres. Needing
to support a wide array of services from high-resolution video streaming to complex AI-driven data processing that require intensive computational power, data centres are rapidly becoming one of the largest consumers of global energy resources. The International Energy Agency has projected that if current trends continue, these data centres could consume over 1,000 terawatt-hours by 2026, a stark increase from the 460 terawatt-hours recorded in 2022.
As data centres continue to grow and adapt to keep up with processing demands, they encounter significant challenges. In an era of unprecedented data throughput, power distribution strategies are evolving to ensure energy efficiency, reduced heat generation, optimised space utilisation, and effective cost management. Traditionally, data centres were designed to handle a power supply of 30-40kW per cabinet. However, the advent of high-power CPUs and GPUs, such as Nvidia’s H100 AI accelerator which contains 80 billion transistors and has a thermal design power (TDP) of 700W, demands a re-evaluation of this standard. These components, characterised by their substantial thermal design power (TDP), push the boundaries of what conventional cooling and power systems can manage. As processing power continues to scale, the power requirements for a single cabinet will exceed 200kW.
16 June 2024
Strategic power distribution network (PDN) adjustments To address these burgeoning power needs, significant adjustments to the power
Figure 1: Data centre power distribution network metrics and their direction of travel
distribution network (PDN) are essential. The PDN must not only be robust but also adaptable to the dynamic changes in data centres. Some key considerations include:
Energy efficiency and cost management: Prioritising energy-efficient solutions helps save energy, reducing operational costs and environmental impact.
Figure 2: The intermediate bus architecture
Components in Electronics
www.cieonline.co.uk
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