An FPGA-Based Architecture for Accelerating Linear Genetic Programming Evaluation

Created by W.Langdon from gp-bibliography.bib Revision:1.8834

@InCollection{Fernandes:2026:raLGP,

• author = "Marina Fernandes and Christopher Crary and Bogdan Burlacu and Wesley Piard and Greg Stitt and Wolfgang Banzhaf and Stephen Kelly",
• title = "An {FPGA}-Based Architecture for Accelerating Linear Genetic Programming Evaluation",
• booktitle = "Recent Advances in Linear Genetic Programming",
• publisher = "Springer",
• year = "2026",
• editor = "Wolfgang Banzhaf and Ting Hu",
• chapter = "7",
• pages = "133--165",
• note = "forthcoming",
• keywords = "genetic algorithms, genetic programming, Linear Genetic Programming, linear evolution processing unit, LEPU, field-programmable gate array, FPGA, hardware acceleration, Alveo V80, BRAM, HBM, DSP, Intron Removal, PROBEN1, Tangled Program Graphs",
• abstract = "our architecture, referred to as the Linear Evolution Processing Unit (LEPU), is competitive with traditional CPU-based LGP implementations in operations per second, while being scalable for deployment on future FPGA technology or dedicated application-specific integrated circuitry. Our experiments show that when compared to a 16-core, 7nm CPU system leveraging AVX2 instructions, our LEPU is up to 50 faster, and 4.5 faster on average. acceleration of more complex forms of GP which build off LGP representations, such as tangled program graphs, which have demonstrated significant potential for rivaling other learning systems (e.g., deep neural networks) in various application",
• notes = "part of \cite{Banzhaf:2026:raLGP_book}",

}

Genetic Programming entries for Marina Fernandes Christopher C Crary Bogdan Burlacu Wesley P Piard Greg Stitt Wolfgang Banzhaf Stephen Kelly

Citations