Profiling Energy Consumption of VMs for Green Cloud Computing

TLDR

The Green Clouds project in the Netherlands pursues a system‑level strategy to green high‑performance computing infrastructures and clouds. This study presents initial results profiling virtual machines on three power metrics—power, power efficiency, and energy—across diverse HPC workloads. The authors built a linear power model that captures the contribution of CPU, memory, and HDD to a single node’s total power consumption while measuring these metrics under various HPC workloads. The results can be incorporated into cluster monitoring systems, enabling a future Green Clouds energy‑savvy scheduler to support system‑level optimization.

Abstract

The Green Clouds project in the Netherlands investigates a system-level approach towards greening High-Performance Computing (HPC) infrastructures and clouds. In this paper we present our initial results in profiling virtual machines with respect to three power metrics, i.e. power, power efficiency and energy, under different high performance computing workloads. We built a linear power model that represents the behavior of a single work node and includes the contribution from individual components, i.e. CPU, memory and HDD, to the total power consumption of a single work node. Our results could be part of a power characterization module integrated into clusters' monitoring systems, future Green Clouds energy-savvy scheduler would use this monitoring system to support system-level optimization.