Improving reliability of embedded systems through dynamic memory manager optimization using grammatical evolution

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@InProceedings{Colmenar:2010:gecco,
  author =       "J. Manuel Colmenar and Jose L. Risco-Martin and 
                 David Atienza and Oscar Garnica and J. Ignacio Hidalgo and 
                 Juan Lanchares",
  title =        "Improving reliability of embedded systems through
                 dynamic memory manager optimization using grammatical
                 evolution",
  booktitle =    "GECCO '10: Proceedings of the 12th annual conference
                 on Genetic and evolutionary computation",
  year =         "2010",
  editor =       "Juergen Branke and Martin Pelikan and Enrique Alba and 
                 Dirk V. Arnold and Josh Bongard and 
                 Anthony Brabazon and Juergen Branke and Martin V. Butz and 
                 Jeff Clune and Myra Cohen and Kalyanmoy Deb and 
                 Andries P Engelbrecht and Natalio Krasnogor and 
                 Julian F. Miller and Michael O'Neill and Kumara Sastry and 
                 Dirk Thierens and Jano {van Hemert} and Leonardo Vanneschi and 
                 Carsten Witt",
  isbn13 =       "978-1-4503-0072-8",
  pages =        "1227--1234",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, SBSE",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Portland, Oregon, USA",
  DOI =          "doi:10.1145/1830483.1830705",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Technology scaling has offered advantages to embedded
                 systems, such as increased performance, more available
                 memory and reduced energy consumption. However, scaling
                 also brings a number of problems like reliability
                 degradation mechanisms. The intensive activity of
                 devices and high operating temperatures are key factors
                 for reliability degradation in latest technology nodes.
                 Focusing on embedded systems, the memory is prone to
                 suffer reliability problems due to the intensive use of
                 dynamic memory on wireless and multimedia applications.
                 In this work we present a new approach to automatically
                 design dynamic memory managers considering reliability,
                 and improving performance, memory footprint and energy
                 consumption. Our approach, based on Grammatical
                 Evolution, obtains a maximum improvement of 39percent
                 in execution time, 38percent in memory usage and
                 50percent in energy consumption over state-of-the-art
                 dynamic memory managers for several real-life
                 applications. In addition, the resulting distributions
                 of memory accesses improve reliability. To the best of
                 our knowledge, this is the first proposal for automatic
                 dynamic memory manager design that considers
                 reliability. Categories and Subject",
  notes =        "evolves garbage collector DMM, C++, p1230 six line BNF
                 grammar given. Reliability fall assumed from increased
                 temperature due to concentrated memory usage. Fitness =
                 weighted sum of run time, bytes and energy used. GEVA
                 applied offline to multi gigabyte profiling logs from
                 VDrift and Physiscs3D.
                 \cites{DBLP:journals/todaes/AtienzaMMSC06}

                 Also known as \cite{1830705} GECCO-2010 A joint meeting
                 of the nineteenth international conference on genetic
                 algorithms (ICGA-2010) and the fifteenth annual genetic
                 programming conference (GP-2010)",
}

Genetic Programming entries for J Manuel Colmenar Jose L Risco-Martin David Atienza Alonso Oscar Garnica Jose Ignacio Hidalgo Perez J Lanchares

Citations