Name: Automatic Tuning of Compilers Using Machine Learning (Springerbriefs in Applied Sciences and Technology) (en Inglés)
Price: 1176.76 MXN
Availability: InStock
Author: Amir H. Ashouri; Gianluca Palermo; John Cavazos
ISBN: 9783319714882

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portada Automatic Tuning of Compilers Using Machine Learning (Springerbriefs in Applied Sciences and Technology) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Amir H. Ashouri; Gianluca Palermo; John Cavazos

Año

2017

Idioma

Inglés

N° páginas

118

Encuadernación

Tapa Blanda

ISBN13

9783319714882

N° edición

Categorías

Inteligencia artificial

Automatic Tuning of Compilers Using Machine Learning (Springerbriefs in Applied Sciences and Technology) (en Inglés)

Amir H. Ashouri; Gianluca Palermo; John Cavazos (Autor) · Springer · Tapa Blanda

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Reseña del libro "Automatic Tuning of Compilers Using Machine Learning (Springerbriefs in Applied Sciences and Technology) (en Inglés)"

This book explores break-through approaches to tackling and mitigating the well-known problems of compiler optimization using design space exploration and machine learning techniques. It demonstrates that not all the optimization passes are suitable for use within an optimization sequence and that, in fact, many of the available passes tend to counteract one another. After providing a comprehensive survey of currently available methodologies, including many experimental comparisons with state-of-the-art compiler frameworks, the book describes new approaches to solving the problem of selecting the best compiler optimizations and the phase-ordering problem, allowing readers to overcome the enormous complexity of choosing the right order of optimizations for each code segment in an application. As such, the book offers a valuable resource for a broad readership, including researchers interested in Computer Architecture, Electronic Design Automation and Machine Learning, as well as computer architects and compiler developers.