Report Number: CS-TR-95-1542
Institution: Stanford University, Department of Computer Science
Title: Parallel Genetic Programming on a Network of Transputers
Author: Koza, John R.
Author: Andre, David
Date: January 1995
Abstract: This report describes the parallel implementation of genetic
programming in the C programming language using a PC 486 type
computer (running Windows) acting as a host and a network of
transputers acting as processing nodes. Using this approach,
researchers of genetic algorithms and genetic programming can
acquire computing power that is intermediate between the
power of currently available workstations and that of
supercomputers at a cost that is intermediate between the
two.
A comparison is made of the computational effort required to
solve the problem of symbolic regression of the Boolean
even-5-parity function with different migration rates.
Genetic programming required the least computational effort
with an 8% migration rate. Moreover, this computational
effort was less than that required for solving the problem
with a serial computer and a panmictic population of the same
size. That is, apart from the nearly linear speed-up in
executing a fixed amount of code inherent in the parallel
implementation of genetic programming, parallelization
delivered more than linear speed-up in solving the problem
using genetic programming.
http://i.stanford.edu/pub/cstr/reports/cs/tr/95/1542/CS-TR-95-1542.pdf