Automatic tuning of compilers using machine learning / Amir H. Ashouri, Gianluca Palermo, John Cavazos, Cristina Silvano.
2018
QA76.76.C65
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Online Access
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Unlimited
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Authorized users
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Can lend chapters, not whole ebooks
Details
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
3319714899 (electronic book)
9783319714882
3319714880
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.
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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Online Access
Record Appears in
Online Resources > Ebooks
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Table of Contents
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.
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.