Energy, exergy and computing efficiency based data center workload and cooling management

The rapidly rising computing workloads in data centers (DCs) have necessitated new approaches to ensure effective performance and resilience that minimize the associated cooling energy. The literature on thermally-aware workload management provides strategies to reduce this energy cost, while typically ignoring the reduction in cooling capacity due to thermodynamic irreversibility and computing performance per unit energy consumption. Hence, we provide an approach that considers coefficient of performance COPc , exergy efficiency ηex , and a new metric, computing performance ratio CPR. In contrast to existing methods that consider one-dimensional workload distributions, the temperature predictions from a physics-based zonal model are used to optimize cooling for two-dimensional workload distributions in a multi-rack DC. The investigation reveals physics associated with two-dimensional workload management for multi-rack DCs, provides a framework for trade-offs between COPc , ηex , and CPR, explains the influence of IT load factor LF on different objectives, and describes how parameters obtained from single- and multi-objective problems can vary. Our findings show that COPc , and ηex can be improved by up to 20% and 8% by regulating the chilled water temperature and airflow setpoints while increasing the LF degrades the CPR by 7.5%. These results enable an extended approach for heterogeneous LF management in large-scale DCs.