How Will AI Change Data Center Architectures?

It is not so clear yet how increasing use of artificial intelligence such as ChatGPT could affect cloud computing and data center architectures. But more edge computing seems a reasonably safe bet.

But man of the other changes might be characterized as augmenting or increasing the value of trends we already can identify. 

“What goes in the racks” is one adaptation. More powerful servers to support high-performance computing seem an obvious inference, though that already is happening for other reasons. Likewise, greater use of parallel processing is likely, along with the use of customized or specialized servers designed to support machine learning operations. 

Those developments arguably are more tactical changes. 

It also is possible that more distributed workloads will be necessary, in part because data might be stored at more locations, including at edge locations. Again, that process already has been underway, driven by the need to support more low-latency processing operations.

But data gravity and edge or distributed locations therefore seem to be opposing trends that will have to be harmonized. 

And while energy consumption already is a big issue, the greater amount of processing makes sustainability even more important as AI operations proliferate. AI operations, being more intensive, also will require more energy, and create more heat, fueling a shift to liquid cooling as well. 

source: Meta 

That, at least, has prompted Meta to consider new data center designs built on liquid cooling. 

Some expect higher degrees of data center automation as well. And, of course, data centers are applying AI to support their own automation efforts and operations.  

As in the past, when each data center essentially takes the form of an ecosystem, so AI operations might push data centers towards a mesh of locations concept, which arguably already has been the case. That data mesh concept includes federated governance, domain-oriented and decentralized data ownership, as well as architecture and much greater self-serve capabilities, says IBM.

So far, the shift to liquid cooling seems the most-discrete change in data center design. Most of the other trends--faster processors, specialized processors, energy efficiency, automation, distributed computing, ecosystems and lower latency--were already underway for other reasons.