Exploring energy aware microarchitectural design space via computationally efficient genetic programming

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

@InProceedings{Halaby:2011:ICEAC,

• author = "Abdallah El-Halaby and Mariette Awad and Rahul Khanna",
• title = "Exploring energy aware microarchitectural design space via computationally efficient genetic programming",
• booktitle = "International Conference on Energy Aware Computing (ICEAC 2011)",
• year = "2011",
• month = "30 " # nov # " - 2 " # dec,
• pages = "1--5",
• address = "Istanbul",
• size = "5 pages",
• abstract = "Efficiently exploring the microarchitectural design space is crucial in order to find promising design subspaces satisfying better power constraints. Based on our previous work on Guided Search Space Genetic Programming (GSS-GP), we introduce a new fitness function based on Fisher Linear Discriminant, in addition to the weighted fitness function designed to improve unbalanced classification accuracy. Experimental results show that GSS-GP outperforms classical GP in both accuracy and convergence times, with a minor class accuracy improvement of 9.05 percentage points. In addition, GSS-GP resulted in a significant reduction of more than 99percent in processing time compared to other robust classifiers like Support Vector Machines.",
• keywords = "genetic algorithms, genetic programming, Fisher linear discriminant, GSS-GP, computationally efficient genetic programming, energy aware microarchitectural design space, guided search space genetic programming, power constraints, support vector machines, weighted fitness function, computer architecture, power aware computing, support vector machines",
• DOI = "doi:10.1109/ICEAC.2011.6136688",
• notes = "Also known as \cite{6136688}",

}

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

Citations