Intelligent Data Centres Issue 88 | Page 22

L A T E S T I N T E L L I G E N C E

6 THINGS TO CONSIDER WHEN DEPLOYING CABINETS FOR AI APPLICATIONS

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6 THINGS TO CONSIDER WHEN DEPLOYING CABINETS FOR AI APPLICATIONS
From physical specifications and load capacity to deployment expectations, traditional data centre cabinets aren’ t designed for the demands of artificial intelligence. To innovate, you need cabinets built for AI.
AI is transforming business operations. As these operations evolve, data centre strategies and infrastructure must adapt to keep pace. By 2030, according to McKinsey, approximately 70 % of data centre capacity demand will come from the need to host advanced AI workloads. As this happens, the demand for dedicated AI infrastructure becomes more critical.
Case in point: data centre cabinets. They’ re no longer simply metal boxes that house IT equipment. Instead, they play a key role in bringing AI initiatives to life. This shift changes everything about them – from physical specifications and load capacity to deployment expectations.
Here are six things to consider when choosing cabinets to support your AI applications.
1 WEIGHT CAPACITY:
HOW MUCH CAN THE CABINET HOLD?
To handle large data sets and complex workloads, AI servers are built differently than typical servers. They feature advanced components like specialized processing units( GPUs and TPUs) and more storage drives to support higher performance requirements, learning capabilities, and faster processing. All this additional hardware increases the weight of an AI server.
Standard cabinets aren’ t designed to support the larger sizes and heavier weights of AI servers. Overloading a cabinet with hardware that exceeds the cabinet’ s weight capacity can create safety issues, lead to equipment damage, and disrupt business operations if the cabinet fails under a higher weight. �
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6 Things to Consider When
DEPLOYING CABINETS FOR AI APPLICATIONS
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