A methodology to automatically optimize dynamic memory managers applying grammatical evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{RiscoMartin:2014:JSS,
  author =       "Jose L. Risco-Martin and J. Manuel Colmenar and 
                 J. Ignacio Hidalgo and Juan Lanchares and Josefa Diaz",
  title =        "A methodology to automatically optimize dynamic memory
                 managers applying grammatical evolution",
  journal =      "Journal of Systems and Software",
  volume =       "91",
  pages =        "109--123",
  year =         "2014",
  ISSN =         "0164-1212",
  DOI =          "doi:10.1016/j.jss.2013.12.044",
  URL =          "http://www.sciencedirect.com/science/article/pii/S016412121400017X",
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 grammatical evolution, Dynamic memory manager, DMM,
                 Heap, malloc, free, Multi-objective optimisation",
  size =         "15 pages",
  abstract =     "Modern consumer devices must execute multimedia
                 applications that exhibit high resource use. In order
                 to efficiently execute these applications, the dynamic
                 memory subsystem needs to be optimised. This complex
                 task can be tackled in two complementary ways:
                 optimising the application source code or designing
                 custom dynamic memory management mechanisms. Currently,
                 the first approach has been well established, and
                 several automatic methodologies have been proposed.
                 Regarding the second approach, software engineers often
                 write custom dynamic memory managers from scratch,
                 which is a difficult and error-prone work. This paper
                 presents a novel way to automatically generate custom
                 dynamic memory managers optimizing both performance and
                 memory usage of the target application. The design
                 space is pruned using grammatical evolution converging
                 to the best dynamic memory manager implementation for
                 the target application. Our methodology achieves
                 important improvements (62.55percent and 30.62percent
                 better on average in performance and memory usage,
                 respectively) when its results are compared to five
                 different general-purpose dynamic memory managers.",
  notes =        "Critical components of hand written BNF grammar
                 altered by memory block sizes and MaxSize extracted
                 from PIN profile of application. Applications in C++
                 hmmer, deall, soplex, calculix, gcc/200, gcc/expr2,
                 gcc/c-typeck and Perl split, diff, spamAssasin Aim
                 replace human written customised garbage collectors
                 HMM. Unclear how deals with more than 256 alternatives
                 in BNF production rule. Compare with Kingsley Lee etc.
                 JECO C++ source code.google.com/p/paba",
}

Genetic Programming entries for Jose L Risco-Martin J Manuel Colmenar Jose Ignacio Hidalgo Perez J Lanchares Josefa Diaz Alvarez

Citations