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Variability-Aware Task Allocation for Energy-Efficient Quality of Service Provisioning in Embedded Streaming Multimedia Applications
July 2012 (vol. 61 no. 7)
pp. 939-953
ASCII Text
x 
 
Francesco Paterna, Andrea Acquaviva, Alberto Caprara, Francesco Papariello, Giuseppe Desoli, Luca Benini, "Variability-Aware Task Allocation for Energy-Efficient Quality of Service Provisioning in Embedded Streaming Multimedia Applications," IEEE Transactions on Computers, vol. 61, no. 7, pp. 939-953, July, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TC.2011.127,
author = {Francesco Paterna and Andrea Acquaviva and Alberto Caprara and Francesco Papariello and Giuseppe Desoli and Luca Benini},
title = {Variability-Aware Task Allocation for Energy-Efficient Quality of Service Provisioning in Embedded Streaming Multimedia Applications},
journal ={IEEE Transactions on Computers},
volume = {61},
number = {7},
issn = {0018-9340},
year = {2012},
pages = {939-953},
doi = {http://doi.ieeecomputersociety.org/10.1109/TC.2011.127},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Computers
TI - Variability-Aware Task Allocation for Energy-Efficient Quality of Service Provisioning in Embedded Streaming Multimedia Applications
IS - 7
SN - 0018-9340
SP939
EP953
EPD - 939-953
A1 - Francesco Paterna,
A1 - Andrea Acquaviva,
A1 - Alberto Caprara,
A1 - Francesco Papariello,
A1 - Giuseppe Desoli,
A1 - Luca Benini,
PY - 2012
KW - Software/software engineering
KW - operating systems
KW - organization and design
KW - real-time systems and embedded systems.
VL - 61
JA - IEEE Transactions on Computers
ER -
 
Francesco Paterna, University of Bologna, Bologna
Andrea Acquaviva, Politecnico di Torino, TORINO
Alberto Caprara, Univeristy of Bologna, Bologna
Francesco Papariello, ST Microelectronics, Cornaredo
Giuseppe Desoli, ST Microelectronics, Cornaredo
Luca Benini, University of Bologna, Bologna
Multimedia streaming applications running on next-generation parallel multiprocessor arrays in sub-45 nm technology face new challenges related to device and process variability, leading to performance and power variations across the cores. In this context, Quality of Service (QoS), as well as energy efficiency, could be severely impacted by variability. In this work, we propose a runtime variability-aware workload distribution technique for enhancing real-time predictability and energy efficiency based on an innovative Linear-Programming + Bin-Packing formulation which can be solved in linear time. We demonstrate our approach on the virtual prototype of a next-generation industrial multicore platform running representative multimedia applications. Experimental results confirm that our technique compensates variability, while improving energy-efficiency and minimizing deadline violations in presence of performance and power variations across the cores. The proposed policy can save up to 33 percent of energy with respect to the state-of-the-art policies and 65 percent of energy with respect to one variability-unaware task allocation policy while providing better QoS.

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Index Terms:
Software/software engineering, operating systems, organization and design, real-time systems and embedded systems.
Citation:
Francesco Paterna, Andrea Acquaviva, Alberto Caprara, Francesco Papariello, Giuseppe Desoli, Luca Benini, "Variability-Aware Task Allocation for Energy-Efficient Quality of Service Provisioning in Embedded Streaming Multimedia Applications," IEEE Transactions on Computers, vol. 61, no. 7, pp. 939-953, July 2012, doi:10.1109/TC.2011.127
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