9783319714882 - automatic tuning of compilers using machine learning di ashouri, amir h. h.; palermo, gianluca; cavazos, john; silvano, cristina (15 risultati)
Automatic Tuning of Compilers Using Machine Learning
Ashouri, Amir Hossein; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
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Automatic Tuning of Compilers Using Machine Learning
Ashouri, Amir Hossein; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Automatic Tuning of Compilers Using Machine Learning (PoliMI SpringerBriefs)
Ashouri, Amir H. H.; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Automatic Tuning of Compilers Using Machine Learning
Ashouri, Amir Hossein; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Automatic Tuning of Compilers Using Machine Learning (SpringerBriefs in Applied Sciences and Technology)
Ashouri, Amir H. H.; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. pp. 135.
Automatic Tuning of Compilers Using Machine Learning
Ashouri, Amir Hossein; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Condizione: As New. Unread book in perfect condition.
Automatic Tuning of Compilers Using Machine Learning
Ashouri, Amir Hossein/ Palermo, Gianluca/ Cavazos, John/ Silvano, Cristina
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 136 pages. 9.25x6.10x0.35 inches. In Stock.
Lingua: Inglese
Editore: Springer, Berlin, Springer International Publishing, Springer, 2018
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 suitab…le 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.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Automatic Tuning of Compilers Using Machine Learning | Amir H. Ashouri (u. a.) | Taschenbuch | xvii | Englisch | 2018 | Springer | EAN 9783319714882 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: pr…eigu.
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Berlin Springer International Publishing Springer Jan 2018, 2018
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 p…asses 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. 118 pp. Englisch.
Automatic Tuning of Compilers Using Machine Learning (SpringerBriefs in Applied Sciences and Technology)
Ashouri, Amir H. H.; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 135.
Automatic Tuning of Compilers Using Machine Learning (SpringerBriefs in Applied Sciences and Technology)
Ashouri, Amir H. H.; Palermo, Gianluca; Cavazos, John; Silvano, Cristina
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 135.
Automatic Tuning of Compilers using Machine Learning
Amir H. Ashouri|Gianluca Palermo|John Cavazos|Cristina Silvano
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Da: moluna, Greven, Germaniamoluna
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 demo…nstrates that not all the optimization passes are suitable for .
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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Paperback. Condizione: new. Paperback. 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 a…nd 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
