Genetic Parallel Programming: Design and Implementation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Cheang:2006:EC,
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author = "Sin Man Cheang and Kwong Sak Leung and Kin Hong Lee",
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title = "Genetic Parallel Programming: Design and
Implementation",
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journal = "Evolutionary Computation",
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year = "2006",
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volume = "14",
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number = "2",
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pages = "129--156",
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month = "Summer",
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keywords = "genetic algorithms, genetic programming, linear
genetic programming, parallel processor architecture,
MIMD, parallel assembly program, ALU MAP, GPP,
Fibonacci recursive sequence",
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ISSN = "1063-6560",
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DOI = "doi:10.1162/evco.2006.14.2.129",
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size = "28 pages",
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abstract = "This paper presents a novel Genetic Parallel
Programming (GPP) paradigm for evolving parallel
programs running on a Multi-Arithmetic-Logic-Unit
(Multi-ALU) Processor (MAP). The MAP is a Multiple
Instruction-streams, Multiple Data-streams (MIMD),
general-purpose register machine that can be
implemented on modern Very Large-Scale Integrated
Circuits (VLSIs) in order to evaluate genetic programs
at high speed. For human programmers, writing parallel
programs is more difficult than writing sequential
programs. However, experimental results show that GPP
evolves parallel programs with less computational
effort than that of their sequential counterparts. It
creates a new approach to evolving a feasible problem
solution in parallel program form and then serialises
it into a sequential program if required. The
effectiveness and efficiency of GPP are investigated
using a suite of 14 well-studied benchmark problems.
Experimental results show that GPP speeds up evolution
substantially.",
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notes = "Table 6 Fibonacci (FIB) experiment 'maximum 200 clock
cycles (each program)'",
- }
Genetic Programming entries for
Ivan Sin Man Cheang
Kwong-Sak Leung
Kin-Hong Lee
Citations