AI factories demand more than isolated subsystem analysis. Thermal constraints at the silicon level propagate through cooling loops, power distribution, and facility infrastructure, while performance changes in any part of the thermal chain can impact reliability, efficiency, and operating costs across the entire facility. In this session, we demonstrate how GT-SUITE enables a unified chip-to-chiller workflow, allowing engineers to model component behavior in high fidelity, optimize cooling system performance within the context of the complete data center, and evaluate how component-level decisions influence overall system operation.

The session will also showcase how integrated electrical, thermal, and controls models can be used to study cross-domain interactions, fine-tune control strategies, and minimize power and water consumption while maintaining reliable performance. Attendees will see how physics-based simulation supports both the design and operational phases of the data center lifecycle, from identifying and characterizing failure modes before deployment to detecting anomalies in live assets and mitigating downtime through real-time monitoring.

Finally, we will demonstrate how GT-SUITE models transition from design tools to operational digital twins, enabling continuous performance tracking, predictive maintenance, and seamless integration with SCADA and facility management systems. Whether you are designing a new facility, qualifying a retrofit, or managing an operational AI cluster, this session highlights how physics-based simulation bridges early-stage design decisions with real-world operational outcomes, helping organizations improve efficiency, reliability, and resilience across the entire data center.