Dynamic Voltage/Frequency Scaling (DVFS) allows designers to improve energy efficiency through adjusting supply voltage at runtime in order to meet the workload demand. Previous works solving real-time DVFS problems often refer to the canonical schedules with the exponential length. Other solutions for online scheduling depend on empirical or stochastic heuristics, which potentially result in frequent fluctuations of voltage/speed scaling. This paper aims at increasing the schedule predictability using period transformation in the pinwheel task model and improves the control on power-awareness by decreasing the speeds of as many tasks as possible to the same level. Experimental results show the maximum energy savings of 6% over the recent Dynamic Power Management (DPM) method and 12% over other slack reclamation algorithms.
Da-Ren CHEN
National Taichung University of Science and Technology
Chiun-Chieh HSU
National Taiwan University of Science and Technology
Hon-Chan CHEN
National Chin-Yi University of Technology
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Da-Ren CHEN, Chiun-Chieh HSU, Hon-Chan CHEN, "A Slack Reclamation Method for Reducing the Speed Fluctuations on the DVFS Real-Time Scheduling" in IEICE TRANSACTIONS on Electronics,
vol. E99-C, no. 8, pp. 918-925, August 2016, doi: 10.1587/transele.E99.C.918.
Abstract: Dynamic Voltage/Frequency Scaling (DVFS) allows designers to improve energy efficiency through adjusting supply voltage at runtime in order to meet the workload demand. Previous works solving real-time DVFS problems often refer to the canonical schedules with the exponential length. Other solutions for online scheduling depend on empirical or stochastic heuristics, which potentially result in frequent fluctuations of voltage/speed scaling. This paper aims at increasing the schedule predictability using period transformation in the pinwheel task model and improves the control on power-awareness by decreasing the speeds of as many tasks as possible to the same level. Experimental results show the maximum energy savings of 6% over the recent Dynamic Power Management (DPM) method and 12% over other slack reclamation algorithms.
URL: https://globals.ieice.org/en_transactions/electronics/10.1587/transele.E99.C.918/_p
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@ARTICLE{e99-c_8_918,
author={Da-Ren CHEN, Chiun-Chieh HSU, Hon-Chan CHEN, },
journal={IEICE TRANSACTIONS on Electronics},
title={A Slack Reclamation Method for Reducing the Speed Fluctuations on the DVFS Real-Time Scheduling},
year={2016},
volume={E99-C},
number={8},
pages={918-925},
abstract={Dynamic Voltage/Frequency Scaling (DVFS) allows designers to improve energy efficiency through adjusting supply voltage at runtime in order to meet the workload demand. Previous works solving real-time DVFS problems often refer to the canonical schedules with the exponential length. Other solutions for online scheduling depend on empirical or stochastic heuristics, which potentially result in frequent fluctuations of voltage/speed scaling. This paper aims at increasing the schedule predictability using period transformation in the pinwheel task model and improves the control on power-awareness by decreasing the speeds of as many tasks as possible to the same level. Experimental results show the maximum energy savings of 6% over the recent Dynamic Power Management (DPM) method and 12% over other slack reclamation algorithms.},
keywords={},
doi={10.1587/transele.E99.C.918},
ISSN={1745-1353},
month={August},}
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TY - JOUR
TI - A Slack Reclamation Method for Reducing the Speed Fluctuations on the DVFS Real-Time Scheduling
T2 - IEICE TRANSACTIONS on Electronics
SP - 918
EP - 925
AU - Da-Ren CHEN
AU - Chiun-Chieh HSU
AU - Hon-Chan CHEN
PY - 2016
DO - 10.1587/transele.E99.C.918
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E99-C
IS - 8
JA - IEICE TRANSACTIONS on Electronics
Y1 - August 2016
AB - Dynamic Voltage/Frequency Scaling (DVFS) allows designers to improve energy efficiency through adjusting supply voltage at runtime in order to meet the workload demand. Previous works solving real-time DVFS problems often refer to the canonical schedules with the exponential length. Other solutions for online scheduling depend on empirical or stochastic heuristics, which potentially result in frequent fluctuations of voltage/speed scaling. This paper aims at increasing the schedule predictability using period transformation in the pinwheel task model and improves the control on power-awareness by decreasing the speeds of as many tasks as possible to the same level. Experimental results show the maximum energy savings of 6% over the recent Dynamic Power Management (DPM) method and 12% over other slack reclamation algorithms.
ER -