Publication Details
Towards Highly Optimized Cartesian Genetic Programming: From Sequential via SIMD and Thread to Massive Parallel Implementation
Cartesian Genetic Programming, Parallel Computing, SIMD,
AVX, Cluster, Combinational Circuit Design
Most implementations of Cartesian genetic programming (CGP) which can be found in
the literature are sequential. However, solving complex design problems by means
of genetic programming requires parallel implementations of search methods and
fitness functions. This paper deals with the design of highly optimized
implementations of CGP and their detailed evaluation in the task of evolutionary
circuit design. Several sequential implementations of CGP have been analyzed and
the effect of various additional optimizations has been investigated.
Furthermore, the parallelism at the instruction, data, thread and process level
has been applied in order to take advantage of modern processor architectures and
computer clusters. Combinational adders and multipliers have been chosen to give
a performance comparison with state of the art methods.
@inproceedings{BUT111521,
author="Radek {Hrbáček} and Lukáš {Sekanina}",
title="Towards Highly Optimized Cartesian Genetic Programming: From Sequential via SIMD and Thread to Massive Parallel Implementation",
booktitle="GECCO '14 Proceedings of the 2014 conference on Genetic and evolutionary computation",
year="2014",
pages="1015--1022",
publisher="Association for Computing Machinery",
address="New York",
doi="10.1145/2576768.2598343",
isbn="978-1-4503-2662-9",
url="http://dl.acm.org/citation.cfm?id=2576768.2598343"
}