Multi-objective adaptive evolutionary strategy for tuning compilations


Autoria(s): Martínez-Álvarez, Antonio; Calvo-Zaragoza, Jorge; Cuenca-Asensi, Sergio; Ortiz García, Andrés; Jimeno-Morenilla, Antonio
Contribuinte(s)

Universidad de Alicante. Departamento de Tecnología Informática y Computación

Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos

UniCAD: Grupo de investigación en CAD/CAM/CAE de la Universidad de Alicante

Reconocimiento de Formas e Inteligencia Artificial

Data(s)

03/06/2014

03/06/2014

10/01/2014

Resumo

Tuning compilations is the process of adjusting the values of a compiler options to improve some features of the final application. In this paper, a strategy based on the use of a genetic algorithm and a multi-objective scheme is proposed to deal with this task. Unlike previous works, we try to take advantage of the knowledge of this domain to provide a problem-specific genetic operation that improves both the speed of convergence and the quality of the results. The evaluation of the strategy is carried out by means of a case of study aimed to improve the performance of the well-known web server Apache. Experimental results show that a 7.5% of overall improvement can be achieved. Furthermore, the adaptive approach has shown an ability to markedly speed-up the convergence of the original strategy.

Identificador

Neurocomputing. 2014, 123: 381-389. doi:10.1016/j.neucom.2013.07.036

0925-2312 (Print)

1872-8286 (Online)

http://hdl.handle.net/10045/37799

10.1016/j.neucom.2013.07.036

Idioma(s)

eng

Publicador

Elsevier

Relação

http://dx.doi.org/10.1016/j.neucom.2013.07.036

Direitos

info:eu-repo/semantics/openAccess

Palavras-Chave #Tuning compilations #Evolutionary search #Genetic algorithm #Adaptive strategy #Multi-objective optimization #NSGA-II #Arquitectura y Tecnología de Computadores #Lenguajes y Sistemas Informáticos
Tipo

info:eu-repo/semantics/article