Adaptive Batch Size CGP: Improving accuracy and runtime for CGP Logic Optimization flow

Created by W.Langdon from gp-bibliography.bib Revision:1.7316

@InProceedings{Martins-Lima:2023:EuroGP,

• author = "Bryan {Martins Lima} and Naiara Sachetti and Augusto Berndt and Cristina Meinhardt and Jonata {Tyska Carvalho}",
• title = "Adaptive Batch Size {CGP}: Improving accuracy and runtime for {CGP} Logic Optimization flow",
• booktitle = "EuroGP 2023: Proceedings of the 26th European Conference on Genetic Programming",
• year = "2023",
• month = "12-14 " # apr,
• editor = "Gisele Pappa and Mario Giacobini and Zdenek Vasicek",
• series = "LNCS",
• volume = "13986",
• publisher = "Springer Verlag",
• address = "Brno, Czech Republic",
• pages = "149--164",
• organisation = "EvoStar, Species",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, CGP, Logic synthesis, Evolutionary algorithms, Approximate Computing",
• isbn13 = "978-3-031-29572-0",
• URL = "https://rdcu.be/c8US8",
• DOI = "doi:10.1007/978-3-031-29573-7_10",
• size = "16 pages",
• abstract = "With the recent advances in the Machine Learning field, alongside digital circuits becoming more complex each day, machine learning based methods are being used in error-tolerant applications to solve the challenges imposed by large integrated circuits, where the designer can obtain a better overall circuit while relaxing its accuracy requirement. One of these methods is the Cartesian Genetic Programming (CGP), a subclass of Evolutionary Algorithms that uses concepts from biological evolution applied in electronic design automation. CGP-based approaches show advantages in the logic learning and logic optimization processes. However, the main challenge of CGP-based flows is the extensive runtime compared to other logic synthesis strategies. We propose a new strategy to tackle this challenge, called Adaptive Batch Size (ABS) CGP, in which the CGP algorithm incrementally improves the fitness estimation of the candidate solutions by using more terms of the truth table for eva",
• notes = "Part of \cite{Pappa:2023:GP} EuroGP'2023 held in conjunction with EvoCOP2023, EvoMusArt2023 and EvoApplications2023",

}

Genetic Programming entries for Bryan Martins Lima Naiara Sachetti Augusto Andre Souza Berndt Cristina Meinhardt Jonata Tyska Carvalho

Citations