JuliaCon 2026

The rapid spread of AI into all aspects of society has led to a corresponding surge in data centers to support the exploding computing demand. Data centers are complex interconnected physical systems with thermal power generation, electrical power conversion, and cooling systems for the compute chips. The compute load that the data center can effectively deliver is a function of the complex response of these systems including the associated controls for the load dispatch strategy and cascaded controls of the various subsystems. System modeling with representation of the physical systems and key controls is a critical tool for understanding the physical response and operation of data centers.

This talk presents two different uses cases for system modeling in data centers. The first case focuses on data center operation. High level transient models in Dyad, Julia, and ModelingToolkit of the data center load, power generation, and electrical system are shown focusing primarily on power demand and supply and high-level control and dispatch. These models are meant to capture the critical interactions between the total power demand from the compute side of the data center and the required power generation provided by the turbines and generators. Different operational strategies for turbine scheduling will be demonstrated to assess their impact on system performance and robustness over different load profiles. These models can address questions regarding the optimal dispatch strategy for the turbines and the impact of different load management strategies on system performance. Models including the effects of battery energy storage systems are developed to assess the impact of battery sizing and control strategies on the data center operation. The impacts of various failures can also be simulated with these models. These system models are suitable for simulations over multiple time scales. Shorter simulations are shown to focus on load planning and the resulting transient power dynamics. Long time horizon simulations (hours, weeks, months) support operational and economic optimization of data centers with SciML techniques.

The second use case focuses on multi-physics models for data center cooling. Transient models for data center cooling are demonstrated that capture the thermal interactions between the CPU and GPU and the resulting cooling system. Built from reusable components in Dyad, these models are full physical models that capture the lumped thermal dynamics of the chips and cooling system at the server and rack level. They can provide temperature predictions at the lumped chip level to support a higher level of fidelity in the system simulations and for load planning. These models are still suitable for long time horizon simulations as they are lumped but discretized.