Paper Info
Title
Parallel programs are more evolvable than sequential programs
Abstract
This paper presents a novel phenomenon of the Genetic Parallel Programming (GPP) paradigm - the GPP accelerating phenomenon. GPP is a novel Linear Genetic Programming representation for evolving parallel programs running on a Multi-ALU Processor (MAP). We carried out a series of experiments on GPP with different number of ALUs. We observed that parallel programs are more evolvable than sequential programs. For example, in the Fibonacci sequence regression experiment, evolving a 1-ALU sequential program requires 51 times on average of the computational effort of an 8-ALU parallel program. This paper presents three benchmark problems to show that the GPP can accelerate evolution of parallel programs. Due to the accelerating evolution phenomenon of GPP over sequential program evolution, we could increase the normal GP's evolution efficiency by evolving a parallel program by GPP and if there is a need, the evolved parallel program can be translated into a sequential program so that it can run on conventional hardware.
Year
DOI
Venue
2003
10.1007/3-540-36599-0_10
EuroGP
Keywords
Field
DocType
genetic parallel programming,novel phenomenon,1-alu sequential program,8-alu parallel program,evolution efficiency,accelerating evolution phenomenon,sequential program,parallel program,novel linear genetic programming,sequential program evolution,genetics,fibonacci sequence
Computer science,Theoretical computer science,Genetic programming,Linear programming,Linear genetic programming,Symbolic regression,Program evolution,Genetic algorithm,Distributed computing,Fibonacci number
Conference
Volume
ISSN
ISBN
2610
0302-9743
3-540-00971-X
Citations 
PageRank 
References 
10
0.95
7
Authors
3
Name
Order
Citations
PageRank
Kwong-Sak Leung11887205.58
Kin Hong Lee2506.56
Sin Man Cheang3445.14