Multi-objective adaptive evolutionary strategy for tuning compilations

NEUROCOMPUTING

卷:123

Article

Martinez-Alvarez, Antonio¹  Calvo-Zaragoza, Jorge¹  Cuenca-Asensi, Sergio¹  Ortiz, Andres²  Jimeno-Morenilla, Antonio¹ 

[1] Univ Alicante, Comp Technol Dept, Alicante 03690, Spain

[2] Univ Malaga, Dept Commun Engn, E-29071 Malaga, Spain

关键词: Tuning compilations;    Evolutionary search;    Genetic algorithm;    Adaptive strategy;    Multi-objective optimization;    NSGA-II;   

DOI  :  10.1016/j.neucom.2013.07.036

来源: Elsevier

【 摘 要 】

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. (C) 2013 Elsevier B.V. All rights reserved.

【 授权许可】

Free