Guided Search Space Genetic Programming for identifying energy aware microarchitectural designs

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Halaby:2010:ICEAC,

• author = "A. Halaby and M. Awad and R. Khanna",
• title = "Guided Search Space Genetic Programming for identifying energy aware microarchitectural designs",
• booktitle = "2010 International Conference on Energy Aware Computing (ICEAC)",
• year = "2010",
• month = "16-18 " # dec,
• keywords = "genetic algorithms, genetic programming, GSS-GP, energy aware microarchitectural design, fitness function, guided search space genetic programming, machine learning technique, resource use, convergence, learning (artificial intelligence), power aware computing, search problems",
• DOI = "doi:10.1109/ICEAC.2010.5702307",
• abstract = "Genetic Programming (GP) is being proposed as a machine learning technique in design space exploration. An evolutionary but heuristic approach by default, GP basically searches the whole input space for suboptimal values, which often translates into long convergence times, more processing and thus inefficient resource usage. We propose in this paper a Guided Search Space GP (GSS-GP) approach that improves convergence time and accuracy because of the limited search space it uses and the fitness function designed to account for the class disproportionality. Experimental results to identify energy aware microarchitectural designs show the merit of GSS-GP and motivate follow on research.",
• notes = "fixed representation classifier. Electrical & Computer Engineering, American University of Beirut, Beirut, Lebanon. Also known as \cite{5702307}",

}

Genetic Programming entries for Abdallah El-Halaby Mariette Awad Rahul Khanna

Citations