Combining Machine Learning with a Genetic Algorithm to Find Good Complier Optimizations Sequences

Nilton Luiz Queiroz Junior, Luis Gustavo Araujo Rodriguez, Anderson Faustino da Silva

2017

Abstract

Artificial Intelligence is a strategy applied in several problems in computer science. One of them is to find good compilers optimizations sequences for programs. Currently, strategies such as Genetic Algorithms and Machine Learning have been used to solve it. This article propose an approach that combines both, Machine Learning and Genetic Algorithms, to solve this problem. The obtained results indicate that the proposed approach achieves performance up to 3.472% over Genetic Algorithms and 4.94% over Machine Learning.

Paper Citation

in Harvard Style

Queiroz Junior N., Rodriguez L. and da Silva A. (2017). Combining Machine Learning with a Genetic Algorithm to Find Good Complier Optimizations Sequences . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 397-404. DOI: 10.5220/0006270403970404

in Bibtex Style

@conference{iceis17,
author={Nilton Luiz Queiroz Junior and Luis Gustavo Araujo Rodriguez and Anderson Faustino da Silva},
title={Combining Machine Learning with a Genetic Algorithm to Find Good Complier Optimizations Sequences},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={397-404},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006270403970404},
isbn={978-989-758-247-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Combining Machine Learning with a Genetic Algorithm to Find Good Complier Optimizations Sequences
SN - 978-989-758-247-9
AU - Queiroz Junior N.
AU - Rodriguez L.
AU - da Silva A.
PY - 2017
SP - 397
EP - 404
DO - 10.5220/0006270403970404