A SIMD Interpreter for Linear Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8194

@InProceedings{Ababsa:2022:ISNIB,

• author = "Tarek Ababsa",
• booktitle = "2022 International Symposium on iNnovative Informatics of Biskra (ISNIB)",
• title = "A {SIMD} Interpreter for Linear Genetic Programming",
• year = "2022",
• abstract = "Genetic programming (GP) has been applied as an automatic programming tool to solve various kinds of problems by genetically breeding a population of computer programs using biologically inspired operations. However, it is well known as a computationally demanding approach with a significant potential of parallelization. In this paper, we emphasize parallelizing the evaluation of genetic programs on Graphics Processing Unit (GPU). We used a compact representation for genotypes. This representation is a memory-efficient method that allows efficient evaluation of programs. Our implementation clearly distinguishes between an individual's genotype and phenotype. Thus, the individuals are represented as linear entities (arrays of 32 bits integers) that are decoded and expressed just like nonlinear entities (trees).",
• keywords = "genetic algorithms, genetic programming, linear genetic programming, GPU, Graphics, Automatic programming, Sociology, Graphics processing units, Arrays, Statistics, Parallel Processing, GPGPU, symbolic regression",
• DOI = "doi:10.1109/ISNIB57382.2022.10075819",
• month = dec,
• notes = "Also known as \cite{10075819}",

}

Genetic Programming entries for Tarek Ababsa

Citations