Applying Genetic Parallel Programming to Synthesize Combinational Logic Circuits
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gp-bibliography.bib Revision:1.8098
- @Article{Cheang:2007:tec,
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author = "Sin Man Cheang and Kin Hong Lee and Kwong Sak Leung",
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title = "Applying Genetic Parallel Programming to Synthesize
Combinational Logic Circuits",
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journal = "IEEE Transactions on Evolutionary Computation",
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year = "2007",
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volume = "11",
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number = "4",
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pages = "503--520",
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month = aug,
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keywords = "genetic algorithms, genetic programming, FPGA, Circuit
design, digital circuits, evolvable hardware, parallel
programming",
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ISSN = "1389-2576",
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DOI = "doi:10.1109/TEVC.2006.884044",
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size = "18 pages",
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abstract = "Experimental results show that parallel programs can
be evolved more easily than sequential programs in
genetic parallel programming (GPP). GPP is a novel
genetic programming paradigm which evolves parallel
program solutions. With the rapid development of
lookup-table-based (LUT-based) field programmable gate
arrays (FPGAs), traditional circuit design and
optimisation techniques cannot fully exploit the LUTs
in LUT-based FPGAs. Based on the GPP paradigm, we have
developed a combinational logic circuit learning
system, called GPP logic circuit synthesiser (GPPLCS),
in which a multilogic-unit processor is used to
evaluate LUT circuits. To show the effectiveness of the
GPPLCS, we have performed a series of experiments to
evolve combinational logic circuits with two- and
four-input LUTs. In this paper, we present eleven
multi-output Boolean problems and their evolved
circuits. The results show that the GPPLCS can evolve
more compact four-input LUT circuits than the
well-known LUT-based FPGA synthesis algorithms.",
- }
Genetic Programming entries for
Ivan Sin Man Cheang
Kin-Hong Lee
Kwong-Sak Leung
Citations