Multi-objective adaptive evolutionary strategy for tuning compilations
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 |
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Data(s) |
03/06/2014
03/06/2014
10/01/2014
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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 |