How AI data centres cut annual water consumption by 50%

· Source: AI Magazine · Field: Technology & Digital — Cloud Computing & IT Infrastructure, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

Schneider Electric asserts that AI data centers can cut annual water consumption by up to 50% by adopting advanced liquid cooling systems instead of traditional air chillers. Tuan Hoang, Head of Cooling Technology and Product Development, emphasizes that "zero water is needed to cool AI data centers" and that water consumption is a "geographical choice." Modelled scenarios for facilities in Dallas and Paris demonstrated significant reductions: Dallas saw a 48% drop from 382,000 to 197,000 cubic meters per year, while Paris achieved a 53% reduction from 108,000 to 51,000 cubic meters. The company's Uniflair XCA line, featuring air-cooled chillers with up to 2.4MW capacity and a closed-loop design, exemplifies a water-free heat rejection strategy. Rich Whitmore, CEO of Motivair by Schneider Electric, states that liquid cooling is now essential for AI racks approaching 400kW.

Key takeaway

For AI Architects and MLOps Engineers planning or upgrading data centers for high-density AI workloads, you should re-evaluate liquid cooling strategies. Adopting closed-loop liquid cooling systems, such as Schneider Electric's Uniflair XCA line, allows you to meet the thermal demands of AI racks approaching 400kW while significantly reducing or eliminating annual water consumption. This approach can improve site selection flexibility and enhance your facility's environmental sustainability profile.

Key insights

Liquid cooling for AI data centers can eliminate water consumption, addressing environmental concerns for high-density compute.

Principles

Method

Transition from traditional air cooling to advanced liquid architectures, specifically employing closed-loop systems that radiate heat externally using factory-sealed cooling fluid.

In practice

Topics

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Architect, MLOps Engineer, IT Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.