{"id":21669,"date":"2023-10-05T12:42:25","date_gmt":"2023-10-05T11:42:25","guid":{"rendered":"https:\/\/www.onnecgroup.com\/?p=21669"},"modified":"2024-02-15T09:40:26","modified_gmt":"2024-02-15T09:40:26","slug":"the-design-dilemma-reimagining-data-centres-for-the-ai-era","status":"publish","type":"post","link":"https:\/\/www.onnecgroup.com\/de-DE\/2023\/10\/05\/the-design-dilemma-reimagining-data-centres-for-the-ai-era\/","title":{"rendered":"The Design Dilemma: Reimagining Data Centres for the AI Era"},"content":{"rendered":"\n
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The design dilemma: reimagining data centres for the AI era<\/strong><\/h1>\n\n\n\n

By Niklas Lindqvist, General Manager, Onnec Nordics<\/strong><\/p>\n\n\n\n

Artificial Intelligence (AI) has hit the mainstream. New tools and applications, such as text and video generation, are growing in popularity and have the potential to supercharge business growth and productivity.<\/p>\n\n\n\n

With 35% of global organisations adopting AI<\/a>, and worldwide AI spend set to reach $300bn by 2026<\/a>, we have now reached a tipping point where AI adoption is becoming exponential. But to realise AI ambitions, data centres will be under huge pressure to meet skyrocketing demand \u2013 operators will want to ensure business continuity, but also gain and retain customers. AI raises major implications over how to design the data centre of the future. In the rush to meet demand, its important operators tread carefully to avoid making an expensive mistake.<\/p>\n\n\n\n

Irreversible implications<\/strong><\/p>\n\n\n\n

AI has taken centre stage and is rewriting everything we know about data centre design. To cater for rising AI demand, operators have been completely rethinking their design approaches. In fact, some hyperscalers hit pause<\/a> on projects until they better understood the requirements for AI workloads.<\/p>\n\n\n\n

The key area under consideration comes down to AI-compute. Data centres have traditionally relied on Central Processing Units (CPU) powered racks. But to cater for AI, Graphics Processing Units (GPU) will be required, which consume more power, generate additional heat, and occupy more space.<\/p>\n\n\n\n

This makes decisions regarding the CPU versus GPU allocation during the initial design stage crucial, as essential infrastructure, such as power, cooling or cabling can be difficult to replace once built. To effectively cater to demand, operators need to get the CPU\/GPU split right. But to do that, they need a clearer picture of demand to establish whether existing designs, infrastructure and cabling can cope.<\/p>\n\n\n\n

Re-designing for AI<\/strong><\/p>\n\n\n\n

Understanding this split will give operators a much clearer view of design requirements and the infrastructure required. AI will dramatically change design requirements in multiple areas, such as:<\/p>\n\n\n\n