Investigating the potential of application-centric aggressive power management for HPC workloads

I. Rodero, S. Chandra, M. Parashar, R. Muralidhar, H. Seshadri, S. Poole

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations

Abstract

Energy efficiency of large-scale data centers is becoming a major concern not only for reasons of energy conservation, failures, and cost reduction, but also because such systems are soon reaching the limits of power available to them. Like High Performance Computing (HPC) systems, large-scale cluster-based data centers can consume power in megawatts, and of all the power consumed by such a system, only a fraction is used for actual computations. In this paper, we study the potential of application-centric aggressive power management of data center's resources for HPC workloads. Specifically, we consider power management mechanisms and controls (currently or soon to be) available at different levels and for different subsystems, and leverage several innovative approaches that have been taken to tackle this problem in the last few years, can be effectively used in a applicationaware manner for HPC workloads. To do this, we first profile standard HPC benchmarks with respect to behaviors, resource usage and power impact on individual computing nodes. Based on a power and latency model and the workload profiles, we develop an algorithm that can improve energy efficiency with little or no performance loss. We then evaluate our proposed algorithm through simulations using empirical power characterization and quantification. Finally, we validate the simulation results with actual executions on real hardware. The obtained results show that by using application aware power management, we can reduce the average energy consumption without significant penalty in performance. This motivates us to investigate autonomic approaches for application-aware aggressive power management and cross layer and cross function predictive subsystem level power management for large-scale data centers.

Original languageEnglish (US)
Title of host publication17th International Conference on High Performance Computing, HiPC 2010
DOIs
StatePublished - 2010
Event17th International Conference on High Performance Computing, HiPC 2010 - Goa, India
Duration: Dec 19 2010Dec 22 2010

Publication series

Name17th International Conference on High Performance Computing, HiPC 2010

Other

Other17th International Conference on High Performance Computing, HiPC 2010
CountryIndia
CityGoa
Period12/19/1012/22/10

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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