Evolutionary design of the memory subsystem

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Josefa {Diaz Alvarez} and Jose L. Risco-Martin and 
                 J. Manuel Colmenar",
  title =        "Evolutionary design of the memory subsystem",
  journal =      "Applied Soft Computing",
  year =         "2018",
  volume =       "62",
  pages =        "1088--1101",
  month =        jan,
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 evolution, NSGA-II, SBSE, Hardware design optimization,
                 Memory subsystem design",
  ISSN =         "1568-4946",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1568494617305860",
  DOI =          "doi:10.1016/j.asoc.2017.09.047",
  abstract =     "The memory hierarchy has a high impact on the
                 performance and power consumption in the system.
                 Moreover, current embedded systems, included in mobile
                 devices, are specifically designed to run multimedia
                 applications, which are memory intensive. This
                 increases the pressure on the memory subsystem and
                 affects the performance and energy consumption. In this
                 regard, the thermal problems, performance degradation
                 and high energy consumption, can cause irreversible
                 damage to the devices. We address the optimization of
                 the whole memory subsystem with three approaches
                 integrated as a single methodology. Firstly, the
                 thermal impact of register file is analysed and
                 optimized. Secondly, the cache memory is addressed by
                 optimizing cache configuration according to running
                 applications and improving both performance and power
                 consumption. Finally, we simplify the design and
                 evaluation process of general-purpose and customized
                 dynamic memory manager, in the main memory. To this
                 aim, we apply different evolutionary algorithms in
                 combination with memory simulators and profiling tools.
                 This way, we are able to evaluate the quality of each
                 candidate solution and take advantage of the
                 exploration of solutions given by the optimization
                 algorithm. We also provide an experimental experience
                 where our proposal is assessed using well-known
                 benchmark applications.",

Genetic Programming entries for Josefa Diaz Alvarez Jose L Risco-Martin J Manuel Colmenar