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DReAM: Per-Task DRAM Energy Metering in Multicore Systems

  • Qixiao Liu
  • Miquel Moreto
  • Jaume Abella
  • Francisco J. Cazorla
  • Mateo Valero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8632)

Abstract

Interaction across applications in DRAM memory impacts its energy consumption. This paper makes the case for accurate per-task DRAM energy metering in multicores, which opens new paths to energy/performance optimizations, such as per-task energy-aware task scheduling and energy-aware billing in datacenters. In particular, the contributions of this paper are (i) an ideal per-task energy metering model for DRAM memories; (ii) DReAM, an accurate, yet low cost, implementation of the ideal model (less than 5% accuracy error when 16 tasks share memory); and (iii) a comparison with standard methods (even distribution and access-count based) proving that DReAM is more accurate than these other methods.

Keywords

Memory Access Multicore System Memory Controller Average Prediction Error Last Level Cache 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Qixiao Liu
    • 1
    • 2
  • Miquel Moreto
    • 1
    • 2
  • Jaume Abella
    • 1
  • Francisco J. Cazorla
    • 1
    • 2
    • 3
  • Mateo Valero
    • 1
    • 2
  1. 1.Barcelona Supercomputing CenterBarcelonaSpain
  2. 2.Universitat Politecnica de CatalunyaBarcelonaSpain
  3. 3.Spanish National Research Council (IIIA-CSIC)BarcelonaSpain

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