Exploring the space of optimization sequences for code-size reduction: insights and tools
Author:
Affiliation:
1. State University of Maringá, Brazil
2. Federal University of Minas Gerais, Brazil
Funder
Fundação de Amparo à Pesquisa do Estado de Minas Gerais
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3446804.3446849
Reference25 articles.
1. Using Machine Learning to Focus Iterative Optimization
2. Amir H. Ashouri William Killian John Cavazos Gianluca Palermo and Cristina Silvano. 2018. A Survey on Compiler Autotuning Using Machine Learning. Comput. Surv. 51 5 ( 2018 ) 96 : 1-96 : 42. htps: //doi.org/10.1145/3197978 Amir H. Ashouri William Killian John Cavazos Gianluca Palermo and Cristina Silvano. 2018. A Survey on Compiler Autotuning Using Machine Learning. Comput. Surv. 51 5 ( 2018 ) 96 : 1-96 : 42. htps: //doi.org/10.1145/3197978
3. A parallel global multiobjective framework for optimization: pagmo
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