H. Juille, and J. Pollack. Advances in Genetic Programming 2, chapter 17, MIT Press, Cambridge, MA, USA, (1996)
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 Koza95 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 tufts95, 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.
%0 Book Section
%1 pollack:1996:aigp2
%A Juille, Hugues
%A Pollack, Jordan B.
%B Advances in Genetic Programming 2
%C Cambridge, MA, USA
%D 1996
%E Angeline, Peter J.
%E Kinnear, Jr., K. E.
%I MIT Press
%K algorithms, coevolution, competitive fitness, genetic problem programming, spirals
%P 339--358
%T Massively Parallel Genetic Programming
%U http://www.demo.cs.brandeis.edu/papers/gp2.ps
%X 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 Koza95 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 tufts95, 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.
%& 17
%@ 0-262-01158-1
@incollection{pollack:1996:aigp2,
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 [Koza95] 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 [tufts95], 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.
},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Cambridge, MA, USA},
author = {Juille, Hugues and Pollack, Jordan B.},
biburl = {https://www.bibsonomy.org/bibtex/2b3c982cd7a0845907b05418ab9a48244/brazovayeye},
booktitle = {Advances in Genetic Programming 2},
chapter = 17,
editor = {Angeline, Peter J. and {Kinnear, Jr.}, K. E.},
interhash = {0d4b0a6f816ba93707bdc86b8c9cdd8c},
intrahash = {b3c982cd7a0845907b05418ab9a48244},
isbn = {0-262-01158-1},
keywords = {algorithms, coevolution, competitive fitness, genetic problem programming, spirals},
notes = {tic-tak-toe, intertwined spirals, coevolution},
pages = {339--358},
publisher = {MIT Press},
size = {21 pages},
timestamp = {2008-06-19T17:42:43.000+0200},
title = {Massively Parallel Genetic Programming},
url = {http://www.demo.cs.brandeis.edu/papers/gp2.ps},
year = 1996
}