Runtime Voltage/Frequency Scaling for Energy-Aware Streaming Applications
Gruian, Flavius LU
(2012)
46th Annual Asilomar Conference on Signals, Systems, and Computers, 2012
p.1439-1443
- Abstract
- Power and energy consumption, today essential in all types of systems, can be reduced by scaling the voltage/frequency at runtime and/or powering down idle components.
Efficient management requires not only pertinent decisions, but also early access to workload information, as well as domain specific solutions. This paper focuses on runtime energy management for streaming applications running on multiprocessor platforms with dynamic voltage/frequency (speed) scaling capabilities.
Our energy management occurs at processor level, and employs a number of orthogonal techniques based on hints gathered from load history, buffer pressure and future workload estimates.
The manager operates both through speed adjustments... (More) - Power and energy consumption, today essential in all types of systems, can be reduced by scaling the voltage/frequency at runtime and/or powering down idle components.
Efficient management requires not only pertinent decisions, but also early access to workload information, as well as domain specific solutions. This paper focuses on runtime energy management for streaming applications running on multiprocessor platforms with dynamic voltage/frequency (speed) scaling capabilities.
Our energy management occurs at processor level, and employs a number of orthogonal techniques based on hints gathered from load history, buffer pressure and future workload estimates.
The manager operates both through speed adjustments and priorities. A preliminary evaluation based on a high-level simulation of an MPEG-4 SP decoder, shows that a combination of specific and generic techniques is the closest to an ideal energy lower bound. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3210086
- author
- Gruian, Flavius
LU
- organization
- publishing date
- 2012
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)
- pages
- 1439 - 1443
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 46th Annual Asilomar Conference on Signals, Systems, and Computers, 2012
- conference location
- Pacific Grove, California, United States
- conference dates
- 2012-11-04 - 2012-11-07
- external identifiers
-
- wos:000320768400266
- scopus:84876253227
- ISSN
- 1058-6393
- ISBN
- 978-1-4673-5051-8
- 978-1-4673-5050-1
- DOI
- 10.1109/ACSSC.2012.6489264
- project
- High Performance Embedded Computing
- language
- English
- LU publication?
- yes
- id
- fec9b26c-daf1-447d-81e1-c7a5881fd1b8 (old id 3210086)
- date added to LUP
- 2016-04-01 14:20:50
- date last changed
- 2024-01-10 02:30:14
@inproceedings{fec9b26c-daf1-447d-81e1-c7a5881fd1b8,
abstract = {{Power and energy consumption, today essential in all types of systems, can be reduced by scaling the voltage/frequency at runtime and/or powering down idle components.<br/><br>
Efficient management requires not only pertinent decisions, but also early access to workload information, as well as domain specific solutions. This paper focuses on runtime energy management for streaming applications running on multiprocessor platforms with dynamic voltage/frequency (speed) scaling capabilities. <br/><br>
Our energy management occurs at processor level, and employs a number of orthogonal techniques based on hints gathered from load history, buffer pressure and future workload estimates.<br/><br>
The manager operates both through speed adjustments and priorities. A preliminary evaluation based on a high-level simulation of an MPEG-4 SP decoder, shows that a combination of specific and generic techniques is the closest to an ideal energy lower bound.}},
author = {{Gruian, Flavius}},
booktitle = {{Proceedings of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)}},
isbn = {{978-1-4673-5051-8}},
issn = {{1058-6393}},
language = {{eng}},
pages = {{1439--1443}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Runtime Voltage/Frequency Scaling for Energy-Aware Streaming Applications}},
url = {{https://lup.lub.lu.se/search/files/3925389/3210093.pdf}},
doi = {{10.1109/ACSSC.2012.6489264}},
year = {{2012}},
}