pCGP: A Parallel Implementation of Cartesian Genetic Program-ming for Combinatorial Circuit Design and Time-Series Prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Manazir:2022:ICECET,

• author = "Abdul Manazir and Khalid Raza",
• booktitle = "2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)",
• title = "p{CGP:} A Parallel Implementation of Cartesian Genetic Program-ming for Combinatorial Circuit Design and Time-Series Prediction",
• year = "2022",
• abstract = "Cartesian Genetic Programming (CGP), a variant of genetic programming, is computationally extensive where its runtime is dominated by fitness evaluation, especially when the genotypes are complex. In order to speed up the execution, multiple offspring can be evaluated in parallel on multiple processing units. This paper presents a parallel implementation of CGP, called pCGP, using a multiple-threading scheme. The performance of pCGP is tested on two different standard benchmark datasets: i) classical digital circuit design problem, and ii) time-series dataset of monthly total sunspot number. The results show a significant reduction in the mean evolution time of parallel multi-threaded implementation over the serial single-threaded version of standard CGP. Hence, pCGP can be used for faster convergence in a complex problem having a large search space.",
• keywords = "genetic algorithms, genetic programming, Cartesian genetic programming",
• DOI = "doi:10.1109/ICECET55527.2022.9872630",
• month = jul,
• notes = "Also known as \cite{9872630}",

}

Genetic Programming entries for Abdul Manazir Khalid Raza

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