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OverviewThis 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. Full Product DetailsAuthor: Amir H. Ashouri , Gianluca Palermo , John Cavazos , Cristina SilvanoPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 1st ed. 2018 Weight: 0.454kg ISBN: 9783319714882ISBN 10: 3319714880 Pages: 118 Publication Date: 19 January 2018 Audience: College/higher education , Professional and scholarly , Postgraduate, Research & Scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |