@article{ab70c541b3be495ea37983dbddf0e51c,
title = "Special issue on energy reduction techniques for exa-scale computing: theory and practice",
keywords = "AutoTuning, Energy Efficiency, Energy Prediction, Tools",
author = "Shajulin Benedict and Michael Gerndt and Siegfried Benkner",
note = "Funding Information: Paper 3: A few dynamic regression model based prediction approaches were proposed by Rejitha et al. The approach targeted CUDA based applications on GPGPU architectures. The work was carried out at the HPCCLoud Research Laboratory, India, as part of the Energy Tuning of Scientific Applications (EASE) project—an Indo-Austrian DST-FWF funded project. ",
year = "2017",
month = aug,
day = "1",
doi = "10.1007/s00607-017-0570-9",
language = "English",
volume = "99",
pages = "725--726",
journal = "Computing (Vienna/New York)",
issn = "0010-485X",
publisher = "Springer",
number = "8",
}