Learn the value of a tailored approach to AI integration in the data center, exploring the impact of AI integration across four distinct subsystems.
11 pages | File Type: Adobe PDF | Size: 8 MB
EXCERPT:
Introduction
Integrating AI into the data center requires an explosive leap in fiber density and connectivity, with implications for several systems within the facility. Managing such a significant change, as well as anticipating future refresh cycles, is no simple task.
This is why instead of treating facilities as one daunting machine, we’re recommending a more granular approach — breaking down the evolution required across four distinct subsystems, using five key attributes as benchmarks for efficiency and scalability. These five attributes are power, cooling, latency, geography, and speed of deployment.
Adjusting the lens in this manner allows us to zoom in on the actual practical impact of AI integration in each of these spaces, while also setting and sustaining measurable benchmarks for operations at scale. AI's implications for power, cooling, latency, deployment speed, and geography carry forward through the four distinct data center subsystems, affecting change in varying degrees. The subsystems we’ll be examining closely are the DC Interconnect, Entry-Point, Front-End, and Back-End subsystems.