The route to a defect tolerant LUT through artificial evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{Djupdal:2011:GPEM,

• author = "Asbjoern Djupdal and Pauline Haddow",
• title = "The route to a defect tolerant LUT through artificial evolution",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2011",
• volume = "12",
• number = "3",
• pages = "281--303",
• month = sep,
• note = "Special Issue Title: Evolvable Hardware Challenges",
• keywords = "genetic algorithms, genetic programming, evolvable hardware",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-011-9129-2",
• size = "23 pages",
• abstract = "Evolutionary techniques may be applied to search for specific structures or functions, as specified in the fitness function. This paper addresses the challenge of finding an appropriate fitness function when searching for generic rather than specific structures which, when combined with characteristics of defect tolerance on the circuit. Production defects for integrated circuits are expected to increase considerably. To avoid a corresponding drop in yield, improved defect tolerance solutions are needed. In the case of Field Programmable Gate Arrays (FPGAs), the pre-designed gate array provides a bridge between production and the application designers. Thus, introduction of defect tolerant techniques to the FPGA itself could provide a defect free gate array to the application designer, despite production defects. The search for defect tolerance presented herein is directed at finding defect tolerant structures for an important building block of FPGAs: Look-Up Tables (LUTs). Two key approaches are presented: (1) applying evolved generic building blocks to a traditional LUT design and (2) evolving the LUT design directly. The results highlight the fact that evolved generic defect tolerant structures can contribute to highly reliable circuit designs at the expense of area usage. Further, they show that applying such a technique, rather than direct evolution, has benefits with respect to evolvability of larger circuits, again at the expense of area usage.",
• affiliation = "CRAB Lab, IDI, NTNU, Trondheim, Norway",

}

Genetic Programming entries for Asbjoern Djupdal Pauline Haddow

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