Publication Details

Towards Highly Optimized Cartesian Genetic Programming: From Sequential via SIMD and Thread to Massive Parallel Implementation

HRBÁČEK, R.; SEKANINA, L. Towards Highly Optimized Cartesian Genetic Programming: From Sequential via SIMD and Thread to Massive Parallel Implementation. In GECCO '14 Proceedings of the 2014 conference on Genetic and evolutionary computation. New York: Association for Computing Machinery, 2014. p. 1015-1022. ISBN: 978-1-4503-2662-9.
Czech title
K vysoce optimalizovanému Kartézskému genetickému programování: od sekvenční, přes SIMD a vláknově paralelní k masivně paralelní implementaci
Type
conference paper
Language
English
Authors
Hrbáček Radek, Ing., Ph.D. (RG EHW)
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
URL
Keywords

Cartesian Genetic Programming, Parallel Computing, SIMD, AVX, Cluster, Combinational Circuit Design

Abstract

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.

Published
2014
Pages
1015–1022
Proceedings
GECCO '14 Proceedings of the 2014 conference on Genetic and evolutionary computation
ISBN
978-1-4503-2662-9
Publisher
Association for Computing Machinery
Place
New York
DOI
10.1145/2576768.2598343
UT WoS
000364333000127
EID Scopus
2-s2.0-84905707034
BibTeX 
@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"
}
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