Making scheduling cool: temperature-aware workload placement in data centers

TLDR

Trends toward higher‑density computing make heat management a critical challenge in emerging data centers. The study investigates a systems‑level solution that controls heat generation through temperature‑aware workload placement. The authors formulate a thermodynamic model of hot and cold spots, derive scheduling algorithms, and exploit spatially uncorrelated cooling inefficiencies to achieve energy savings. The approach achieves up to a two‑fold reduction in annual cooling costs compared to location‑agnostic workload distribution, without capital investment.

Abstract

Trends towards consolidation and higher-density computing configurations make the problem of heat management one of the critical challenges in emerging data centers. Conventional approaches to addressing this problem have focused at the facilities level to develop new cooling technologies or optimize the delivery of cooling. In contrast to these approaches, our paper explores an alternate dimension to address this problem, namely a systems-level solution to control the heat generation through temperature-aware workload placement. We first examine a theoretic thermodynamic formulation that uses information about steady state hot spots and cold spots in the data center and develop real-world scheduling algorithms. Based on the insights from these results, we develop an alternate approach. Our new approach leverages the non-intuitive observation that the source of cooling inefficiencies can often be in locations spatially uncorrelated with its manifested consequences; this enables additional energy savings. Overall, our results demonstrate up to a factor of two reduction in annual data center cooling costs over location-agnostic workload distribution, purely through software optimizations without the need for any costly capital investment.