Evolving Parallel Machine Programs for a Multi-ALU Processor

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{leung:2002:epmpfamp,

• author = "Kwong Sak Leung and Kin Hong Lee and Sin Man Cheang",
• title = "Evolving Parallel Machine Programs for a {Multi-ALU} Processor",
• booktitle = "Proceedings of the 2002 Congress on Evolutionary Computation CEC2002",
• editor = "David B. Fogel and Mohamed A. El-Sharkawi and Xin Yao and Garry Greenwood and Hitoshi Iba and Paul Marrow and Mark Shackleton",
• pages = "1703--1708",
• year = "2002",
• publisher = "IEEE Press",
• publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
• organisation = "IEEE Neural Network Council (NNC), Institution of Electrical Engineers (IEE), Evolutionary Programming Society (EPS)",
• ISBN = "0-7803-7278-6",
• month = "12-17 " # may,
• notes = "CEC 2002 - A joint meeting of the IEEE, the Evolutionary Programming Society, and the IEE. Held in connection with the World Congress on Computational Intelligence (WCCI 2002)",
• keywords = "genetic algorithms, genetic programming, Factorial sequence, Fibonacci sequence, Sextic function, experiments, genetic parallel programming, linear genetic programming, multi-ALU processor, optimal parallel program evolution, parallel machine programs, program execution speed optimisation, two-phase evolution, instruction sets, multiprocessing systems, parallel programming",
• DOI = "doi:10.1109/CEC.2002.1004499",
• abstract = "This paper proposes a novel genetic parallel programming (GPP) paradigm for evolving optimal parallel programs running on a multi-ALU processor by linear genetic programming. GPP uses a two-phase evolution approach. It evolves completely correct solution programs in the first phase. Then it optimises execution speeds of solution programs in the second phase. Besides, GPP also employs a new genetic operation that swaps sub-instructions of a solution program. Three experiments (Sextic, Fibonacci and Factorial) are given as examples to show that GPP could discover novel parallel programs that fully use the processor's parallelism",

}

Genetic Programming entries for Kwong-Sak Leung Kin-Hong Lee Ivan Sin Man Cheang

Citations