Towards Energy-Proportional Computing Using Subsystem-Level Power Management

TL;DR

This paper explores how subsystem-level power management using Intel RAPL interfaces can improve energy proportionality, performance, and efficiency in enterprise server workloads like SPEC benchmarks.

Contribution

It demonstrates the potential of RAPL-based power limiting to enhance energy proportionality and efficiency for enterprise workloads on modern processors.

Findings

Power limiting improves energy proportionality of server workloads.

Subsystem-level analysis reveals key components affecting power consumption.

RAPL interfaces effectively control power without significant performance loss.

Abstract

Massive data centers housing thousands of computing nodes have become commonplace in enterprise computing, and the power consumption of such data centers is growing at an unprecedented rate. Adding to the problem is the inability of the servers to exhibit energy proportionality, i.e., provide energy-efficient execution under all levels of utilization, which diminishes the overall energy efficiency of the data center. It is imperative that we realize effective strategies to control the power consumption of the server and improve the energy efficiency of data centers. With the advent of Intel Sandy Bridge processors, we have the ability to specify a limit on power consumption during runtime, which creates opportunities to design new power-management techniques for enterprise workloads and make the systems that they run on more energy-proportional. In this paper, we investigate whether it is possible to achieve energy proportionality for enterprise-class server workloads, namely SPECpower_ssj2008 and SPECweb2009 benchmarks, by using Intel's Running Average Power Limit (RAPL) interfaces. First, we analyze the average power consumption of the full system as well as the subsystems and describe the energy proportionality of these components. We then characterize the instantaneous power profile of these benchmarks within different subsystems using the on-chip energy meters exposed via the RAPL interfaces. Finally, we present the effects of power limiting on the energy proportionality, performance, power and energy efficiency of enterprise-class server workloads. Our observations and results shed light on the efficacy of the RAPL interfaces and provide guidance for designing power-management techniques for enterprise-class workloads.