A Power-Aware Run-Time System for High-Performance Computing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Power provisioning for a warehouse-sized computer
Proceedings of the 34th annual international symposium on Computer architecture
Accurate on-line prediction of processor and memoryenergy usage under voltage scaling
EMSOFT '07 Proceedings of the 7th ACM & IEEE international conference on Embedded software
Workload Characterization of the SPECpower_ssj2008 Benchmark
SIPEW '08 Proceedings of the SPEC international workshop on Performance Evaluation: Metrics, Models and Benchmarks
Models and metrics for energy-efficient computer systems
Models and metrics for energy-efficient computer systems
PowerNap: eliminating server idle power
Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
Adagio: making DVS practical for complex HPC applications
Proceedings of the 23rd international conference on Supercomputing
The State of Energy and Performance Benchmarking for Enterprise Servers
Performance Evaluation and Benchmarking
RAPL: memory power estimation and capping
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Delivering energy proportionality with non energy-proportional systems: optimizing the ensemble
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
Power management of online data-intensive services
Proceedings of the 38th annual international symposium on Computer architecture
Power signature analysis of the SPECpower_ssj2008 benchmark
ISPASS '11 Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software
Clearing the clouds: a study of emerging scale-out workloads on modern hardware
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
Pack & Cap: adaptive DVFS and thread packing under power caps
Proceedings of the 44th Annual IEEE/ACM International Symposium on Microarchitecture
Beyond DVFS: A First Look at Performance under a Hardware-Enforced Power Bound
IPDPSW '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
Measuring Energy and Power with PAPI
ICPPW '12 Proceedings of the 2012 41st International Conference on Parallel Processing Workshops
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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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 an enterprise-class server workload, namely SPECpower_ssj2008 benchmark, by using Intel's Running Average Power Limit (RAPL) interfaces. First, we analyze the power consumption and characterize the instantaneous power profile of the SPECpower benchmark within different subsystems using the on-chip energy meters exposed via the RAPL interfaces. We then analyze the impact of RAPL power limiting on the performance, per-transaction response time, power consumption, and energy efficiency of the benchmark under different load levels. 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.