Automatic Tuning of Compilers Using Machine Learning

Name: Automatic Tuning of Compilers Using Machine Learning
SKU: 27262950
Price: 139.99 AUD
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PoliMI SpringerBriefs

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Description

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.

Release date Australia

January 19th, 2018

Author

Series

PoliMI SpringerBriefs

Pages

118

Edition

1st ed. 2018

Audiences

Postgraduate, Research & Scholarly
Professional & Vocational

Illustrations

6 Illustrations, color; 17 Illustrations, black and white; XVII, 118 p. 23 illus., 6 illus. in color.

ISBN-13

9783319714882

Product ID

27262950

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