- author = "Hugues Juille and Jordan B. Pollack",
- title = "Massively Parallel Genetic Programming",
- booktitle = "Advances in Genetic Programming 2",
- publisher = "MIT Press",
- year = "1996",
- editor = "Peter J. Angeline and K. E. {Kinnear, Jr.}",
- pages = "339--357",
- chapter = "17",
- address = "Cambridge, MA, USA",
- keywords = "genetic algorithms, genetic programming, coevolution, competitive fitness, spirals problem",
- ISBN = "0-262-01158-1",
-
URL = "
http://www.demo.cs.brandeis.edu/papers/gp2.pdf",
-
URL = "
http://www.demo.cs.brandeis.edu/papers/gp2.ps.Z",
-
URL = "http://www.demo.cs.brandeis.edu/papers/gp2.ps",
-
URL = "
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6277531",
-
DOI = "
doi:10.7551/mitpress/1109.003.0023",
- size = "19 pages",
-
abstract = "As the field of Genetic Programming (GP) matures and
its breadth of application increases, the need for
parallel implementations becomes absolutely necessary.
The transputer-based system presented in
\cite{andre:1996:aigp2} is one of the rare such
parallel implementations. Until today, no
implementation has been proposed for parallel GP using
a SIMD architecture, except for a data-parallel
approach \cite{tufts93}, although others have exploited
workstation farms and pipelined supercomputers. One
reason is certainly the apparent difficulty of dealing
with the parallel evaluation of different S-expressions
when only a single instruction can be executed at the
same time on every processor. The aim of this chapter
is to present such an implementation of parallel GP on
a SIMD system, where each processor can efficiently
evaluate a different S-expression. We have implemented
this approach on a MasPar MP-2 computer, and will
present some timing results. To the extent that SIMD
machines, like the MasPar are available to offer
cost-effective cycles for scientific experimentation,
this is a useful approach.
",
- notes = "tic-tak-toe, intertwined spirals, coevolution",
