Geração Automática de Benchmarks para Compilação Preditiva

Author:

Kind Cecília1,Coelho Joao1,Kind Bruno1,Pereira Fernando1

Affiliation:

1. Computer Science / UFMG / Compilers Lab, Universidade Federal de Minas Gerais, Brazil

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

ACM

Reference33 articles.

1. Instruction visibility in SPEC CPU2017

2. Amir Hossein Ashouri , Andrea Bignoli , Gianluca Palermo , and Cristina Silvano . 2016. Predictive Modeling Methodology for Compiler Phase-Ordering . In PARMA-DITAM. Association for Computing Machinery , New York, NY, USA , 7–12. https://doi.org/10.1145/2872421.2872424 Amir Hossein Ashouri, Andrea Bignoli, Gianluca Palermo, and Cristina Silvano. 2016. Predictive Modeling Methodology for Compiler Phase-Ordering. In PARMA-DITAM. Association for Computing Machinery, New York, NY, USA, 7–12. https://doi.org/10.1145/2872421.2872424

3. 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. https://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. https://doi.org/10.1145/3197978

4. Gergö Barany . 2017. Liveness-Driven Random Program Generation . In LOPSTR. Springer , Heidelberg, Germany , 112–127. https://doi.org/10.1007/978-3-319-94460-9_7 Gergö Barany. 2017. Liveness-Driven Random Program Generation. In LOPSTR. Springer, Heidelberg, Germany, 112–127. https://doi.org/10.1007/978-3-319-94460-9_7

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