Automatic tuning of compilers using machine learning / Amir H. Ashouri, Gianluca Palermo, John Cavazos, Cristina Silvano.
Ashouri, Amir H., author.; Palermo, Gianluca, author.; Cavazos, John, author.; Silvano, Cristina, author.
2018
QA76.76.C65
Available Online

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Title Automatic tuning of compilers using machine learning / Amir H. Ashouri, Gianluca Palermo, John Cavazos, Cristina Silvano.
ISBN 9783319714899 (electronic book)
3319714899 (electronic book)
9783319714882
3319714880
DOI https://doi.org/10.1007/978-3-319-71489-9
Published Cham, Switzerland : Springer, 2018.
Language English
Description 1 online resource.
Item Number 10.1007/978-3-319-71489-9 doi
Call Number QA76.76.C65
Dewey Decimal Classification 005.4/53
Summary 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (viewed January 5, 2018).
Added Author Ashouri, Amir H., author.
Palermo, Gianluca, author.
Cavazos, John, author.
Silvano, Cristina, author.
Series SpringerBriefs in applied sciences and technology. PoliMI SpringerBriefs.
Available in Other Form Automatic tuning of compilers using machine learning.
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Background
DSE Approach for Compiler Passes
Addressing the Selection Problem of Passes using ML
Intermediate Speedup Prediction for the Phase-ordering Problem
Full-sequence Speedup Prediction for the Phase-ordering Problem
Concluding Remarks.#xE000.

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