Designing data centers with AI and automation in mind

Automation insights

• Building information modeling (BIM) is used in data center design for real-time coordination across disciplines, enhancing efficiency in design, construction and maintenance processes.
• The integration of AI and machine learning in data centers is driving the need for higher density computations, faster networks and complex liquid-cooling systems.

Respondents:

• Amanda Carter, PE, Electrical Discipline Lead, Stantec, Chicago
• Brian A. Rener, PE, LEED AP, Mission Critical Leader, Smith Group, Chicago
• William Kosik, PE, CEM, LEED AP, Lead Senior Mechanical Engineer, kW Mission Critical Engineering, Chicago

Courtesy: WTWH Media

From your experience, what systems within data centers are benefiting from automation that previously might not have?

Brian A. Rener: There is a push in the industry right now for more extensive use of data center information management (DCIM) systems. Right now, DCIM is still in its infancy, and is mostly limited to rack-based information. Eventually we will see this expand to include the entire facility, along with central power and cooling systems with predictive artificial intelligence (AI).

How is building information modeling (BIM) being used in data center design? Describe the project.

William Kosik: We use BIM exclusively for design, construction, operations and maintenance. Using a BIM model provides real-time design information to other disciplines for things like motor location, equipment size and coordination with external consultants. BIM is also used extensively in our peer review and quality assurance/quality control processes. The reviewer’s comments instantly show up on the designer and engineer’s dashboard, eliminating the lag the generally happens when using hand mark-ups.

Can you discuss the role of artificial intelligence and machine learning in enhancing automation and control functionalities within data centers?                       

William Kosik: The tenants in our clients’ data centers are using AI as a part of their business. AI processors create mathematical models and perform high speed complex calculations when solving the models. This process requires higher density computation and faster network speeds unlike most typical data center applications. We are currently seeing AI rack densities 100 kilowatts and greater. The AI clusters are designed in this dense configuration to minimize physical distances between the compute, storage and networking components, located in proximity to each other. This results in highly dense information technology equipment cabinets that require liquid-cooling. This adds an additional level of complexity to the data center cooling systems.

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