A Genetic Programming based approach for efficiently exploring architectural communication design space of MPSoCs

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Esmeraldo:2010:SPL,
  author =       "Guilherme Esmeraldo and Edna Barros",
  title =        "A Genetic Programming based approach for efficiently
                 exploring architectural communication design space of
                 {MPSoCs}",
  booktitle =    "VI Southern Programmable Logic Conference (SPL 2010)",
  year =         "2010",
  month =        "24-26 " # mar,
  pages =        "29--34",
  address =      "Ipojuca, Brazil",
  abstract =     "New integrated circuits technologies and the demand
                 for more complex applications have created
                 Multi-Processor System-on-Chip (MPSoC). MPSoC is a
                 complex integrated circuit, which can be composed of
                 microprocessors, buses, memories and others
                 computational system components. As the number and
                 variety of components of today's MPSoC is increasing,
                 its communication architecture is becoming a limiting
                 factor for applications performance and power
                 consumption. Thus, techniques have been created for
                 exploring the design space in order to find out the
                 best communication architecture for a given
                 application. Such techniques, however, are either
                 inaccurate (by using static analysis based approaches)
                 or very time consuming since each communication
                 configuration of the design space must be simulated (by
                 using simulation models) or estimated (using mixed
                 approaches). This paper presents a new approach to
                 explore the design space of bus-based communication
                 architectures of MPSoCs using Generalised Linear Models
                 and Genetic Programming. By using the proposed
                 approach, some experiments show that it was possible to
                 explore a subset of the design space and to identify
                 the best communication configuration for a given
                 application reducing 90percent of the exploration time
                 with less of 3,8percent mean global error.",
  keywords =     "genetic algorithms, genetic programming, MPSoC,
                 architectural communication design space, generalised
                 linear models, mixed approach, multiprocessor
                 system-on-chip, simulation models, static analysis
                 based approach, multiprocessing systems,
                 system-on-chip",
  DOI =          "doi:10.1109/SPL.2010.5483006",
  notes =        "Also known as \cite{5483006}",
}

Genetic Programming entries for Guilherme Esmeraldo Edna Barros

Citations