Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing Data Centers: A Cyber-Physical Approach

TLDR

High‑performance computing data centers are rapidly expanding, and their thermal management is challenged by hot‑air recirculation and hot‑spot formation. The study demonstrates that minimizing the peak inlet temperature yields the lowest cooling power requirements. A low‑complexity linear heat‑recirculation model defines the MPIT‑TA problem, which is solved by the Xlnt‑GA genetic algorithm and the Xlnt‑SQP sequential quadratic programming method. Simulations show that the proposed approach reduces inlet temperatures by 2–5 °C and cuts cooling energy by 20–30 % compared to other methods, consistently outperforming the existing minimize‑heat‑recirculation algorithm.

Abstract

High-performance computing data centers have been rapidly growing, both in number and size. Thermal management of data centers can address dominant problems associated with cooling such as the recirculation of hot air from the equipment outlets to their inlets and the appearance of hot spots. In this paper, we show through formalization that minimizing the peak inlet temperature allows for the lowest cooling power needs. Using a low-complexity linear heat recirculation model, we define the problem of minimizing the peak inlet temperature within a data center through task assignment (MPIT-TA), consequently leading to minimal cooling-requirement. We also provide two methods to solve the formulation: Xlnt-GA, which uses a genetic algorithm, and Xlnt-SQP, which uses sequential quadratic programming. Results from small-scale data center simulations show that solving the formulation leads to an inlet temperature distribution that, compared to other approaches, is 2 degC to 5 degC lower and achieves about 20 to 30 percent cooling energy savings at common data center utilization rates. Moreover, our algorithms consistently outperform the minimize heat recirculation algorithm, a recirculation-reducing task placement algorithm in the literature.