An evolutionary algorithm for finding optimisation sequences: proposal and experiments

被引：0

作者：

Fabricio Filho, Joao ^{[1
]}

Rodriguez, Luis Gustavo Araujo ^{[2
]}

da Silva, Anderson Faustino ^{[2
]}

机构：

[1] Univ Tecnol Fed Parana, Via Rosalina Maria Santos 1233, Campo Mourao, Brazil

[2] Univ Estadual Maringa, Dept Informat, Colombo Ave 5790,Block C56, Maringa, Parana, Brazil

来源：

INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING | 2020年 / 21卷 / 02期

关键词：

evolutionary algorithms; code optimisation; iterative compilation; machine learning;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：258 / 270

页数：13

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