D2.3 Power models, energy models and libraries for energy-efficient concurrent data structures and algorithms

Phuong Hoai Ha; Vi Ngoc-Nha Tran; Ibrahim Umar; Aras Atalar; Anders Gidenstam; Paul Renaud-Goud; Philippas Tsigas; Ivan Walulya

D2.3 Power models, energy models and libraries for energy-efficient concurrent data structures and algorithms

Distributed, Parallel, and Cluster Computing 2018-02-09 v2

Authors: Phuong Hoai Ha , Vi Ngoc-Nha Tran , Ibrahim Umar , Aras Atalar , Anders Gidenstam , Paul Renaud-Goud , Philippas Tsigas , Ivan Walulya

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Abstract

This deliverable reports the results of the power models, energy models and libraries for energy-efficient concurrent data structures and algorithms as available by project month 30 of Work Package 2 (WP2). It reports i) the latest results of Task 2.2-2.4 on providing programming abstractions and libraries for developing energy-efficient data structures and algorithms and ii) the improved results of Task 2.1 on investigating and modeling the trade-off between energy and performance of concurrent data structures and algorithms. The work has been conducted on two main EXCESS platforms: Intel platforms with recent Intel multicore CPUs and Movidius Myriad platforms.

Keywords

energy-aware computing data processing computer architecture

Cite

@article{arxiv.1801.10556,
  title  = {D2.3 Power models, energy models and libraries for energy-efficient concurrent data structures and algorithms},
  author = {Phuong Hoai Ha and Vi Ngoc-Nha Tran and Ibrahim Umar and Aras Atalar and Anders Gidenstam and Paul Renaud-Goud and Philippas Tsigas and Ivan Walulya},
  journal= {arXiv preprint arXiv:1801.10556},
  year   = {2018}
}

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142 pages

D2.3 Power models, energy models and libraries for energy-efficient concurrent data structures and algorithms

Abstract

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