Optimization of dynamic memory managers for embedded systems using grammatical evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{DBLP:conf/gecco/Risco-MartinAGH09,
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author = "Jose L. Risco-Martin and David Atienza and
Ruben Gonzalo and J. Ignacio Hidalgo",
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title = "Optimization of dynamic memory managers for embedded
systems using grammatical evolution",
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booktitle = "GECCO '09: Proceedings of the 11th Annual conference
on Genetic and evolutionary computation",
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year = "2009",
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editor = "Guenther Raidl and Franz Rothlauf and
Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and
Mauro Birattari and Clare Bates Congdon and
Martin Middendorf and Christian Blum and Carlos Cotta and
Peter Bosman and Joern Grahl and Joshua Knowles and
David Corne and Hans-Georg Beyer and Ken Stanley and
Julian F. Miller and Jano {van Hemert} and
Tom Lenaerts and Marc Ebner and Jaume Bacardit and
Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and
Thomas Jansen and Riccardo Poli and Enrique Alba",
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pages = "1609--1616",
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address = "Montreal",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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month = "8-12 " # jul,
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organisation = "SigEvo",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution, genetic improvement, SBSE",
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isbn13 = "978-1-60558-325-9",
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bibsource = "DBLP, http://dblp.uni-trier.de",
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DOI = "doi:10.1145/1569901.1570116",
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abstract = "New portable consumer embedded devices must execute
multimedia applications (e.g., 3D games, video players
and signal processing software, etc.) that demand
extensive memory accesses and memory usage at a low
energy consumption. Moreover, they must heavily rely on
Dynamic Memory (DM) due to the unpredictability of the
input data and system behavior. Within this context,
consistent design methodologies that can tackle
efficiently the complex DM behavior of these multimedia
applications are in great need. In this article, we
present a novel design framework, based on genetic
programming, which allows us to design custom DM
management mechanisms, optimizing memory accesses,
memory use and energy consumption for the target
embedded system. First, we describe the large design
space of DM management decisions for multimedia
embedded applications. Then, we propose a suitable way
to traverse this design space using grammatical
evolution and construct custom DM managers that
minimize the DM used by these highly dynamic
applications. As a result, our methodology achieves
significant improvements in memory accesses (23percent
less on average), memory usage (38percent less on
average) and energy consumption (reductions of
21percent on average) in real case studies over the
current state-of-the-art DM managers used for these
types of dynamic applications. To the best of our
knowledge, this is the first approach to efficiently
design DM managers for embedded systems using
evolutionary computation and grammar evolution.",
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notes = "Updated by \cite{Colmenar:2010:gecco}
GECCO-2009 A joint meeting of the eighteenth
international conference on genetic algorithms
(ICGA-2009) and the fourteenth annual genetic
programming conference (GP-2009).
ACM Order Number 910092.",
- }
Genetic Programming entries for
Jose L Risco-Martin
David Atienza Alonso
Ruben Gonzalo
Jose Ignacio Hidalgo Perez
Citations