Abstract
Improving energy efficiency to reduce costs in server environments has attracted considerable attention. Considering that processors account for a significant portion of energy consumption in servers, Dynamic Voltage and Frequency Scaling (DVFS) enhances their energy efficiency by adjusting the operational speed and power consumption of processors. Additionally, modern high-end processors extend DVFS functionality not only to core components but also to uncore parts. This is because the increasing complexity and integration of System on Chips (SoCs) have highlighted the substantial energy consumption. However, existing uncore voltage/frequency scaling fails to effectively consider Latency-Critical (LC) applications, leading to sub-optimal energy efficiency or degraded performance. In this paper, we introduce Co-UP, power management that simultaneously scales core and uncore frequencies for latency-critical applications, designed to improve energy efficiency without violating Service Level Objectives (SLOs). To this end, Co-UP incorporates a prediction model that estimates outcomes of energy consumption and performance as uncore and core frequency changes. Based on the estimated gains, Co-UP adjusts to uncore and/or core frequencies to further enhance energy efficiency or performance. This predictive model can rapidly adapt to new and unlearned loads, enabling Co-UP to operate online without any prior profiling. Our experiments show that Co-UP can reduce energy consumption by up to 28.2% compared to existing Intel’s policy and up to 17.6% compared to state-of-the-art power management studies, without SLO violations.
Keywords
Dynamic core management, Latency-critical workloads, Service Level Objectives, Energy efficiency, Data center performance.
Related Research Topics
Cloud Computing & Applications Optimizations
Power/Resource Management for Energy Efficiency of Data-center Servers