Title: An evolutionary algorithm for finding optimisation sequences: proposal and experiments

Authors: João Fabrício Filho; Luis Gustavo Araujo Rodriguez; Anderson Faustino Da Silva

Addresses: Federal University of Technology – Paraná, Via Rosalina Maria dos Santos, 1233 – Campo Mourão, Brazil ' Department of Informatics, State University of Maringá, Colombo Avenue, 5790 – Block C56 – Maringá, Brazil ' Department of Informatics, State University of Maringá, Colombo Avenue, 5790 – Block C56 – Maringá, Brazil

Abstract: Evolutionary algorithms are metaheuristics for solving combinatorial and optimisation problems. A combinatorial problem, important in the context of software development, consists of selecting code transformations that must be utilised by the compiler while generating the target code. The objective of this paper is to propose and evaluate an evolutionary algorithm that is capable of finding an efficient sequence of optimising transformations, which will be used while generating the target code. The results indicate that it is efficient to find good transformation sequences, and a good option to generate databases for machine learning systems.

Keywords: evolutionary algorithms; code optimisation; iterative compilation; machine learning.

DOI: 10.1504/IJCSE.2020.10027432

International Journal of Computational Science and Engineering, 2020 Vol.21 No.2, pp.258 - 270

Received: 26 Jul 2017
Accepted: 11 Jun 2018

Published online: 11 Mar 2020 *

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