Automatic Tuning of Compilers Using Machine Learning
Language: English
Published by Springer-Verlag New York Inc, 2018
- Softcover
- New

Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
AbeBooks seller since January 6, 2003
Condition: New
US$ 88.71
Quantity: 2 available
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136 pages. 9.25x6.10x0.35 inches. In Stock.
Seller Inventory # x-3319714880
- Title
- Automatic Tuning of Compilers Using Machine Learning
- Author
- Ashouri, Amir Hossein/ Palermo, Gianluca/ Cavazos, John/ Silvano, Cristina
- Publisher
- Springer-Verlag New York Inc
- Publication year
- 2018
- Condition
- Brand New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 3319714880
- ISBN 13
- 9783319714882
- Item weight
- 0.2 kilograms
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
Revaluation Books
Exeter, United Kingdom
AbeBooks seller since January 6, 2003
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