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Published by Engineering Science Reference, 2024
ISBN 10: 1668437953 ISBN 13: 9781668437957
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by Engineering Science Reference, 2024
ISBN 10: 1668437953 ISBN 13: 9781668437957
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Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent research efforts in designing and using ML techniques on HPC systems, discusses some of the results achieved thus far by cutting-edge contributions, and highlights some of the ongoing research works in these two fields.
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Researchers are increasingly using machine learning (ML) models to analyze data and simulate complex systems and phenomena. Small-scale computing systems used for training, validation, and testing of these ML models are no longer sufficient for grand-challenge problems characterized by large volumes of data generated at a much higher rate than before, surpassing by far the computing capabilities currently available in many cyberinfrastructure platforms. By associating high-performance computing (HPC) with ML environments, scientists and engineers would be able to enhance not only the scalability but also the performance of their predictive ML models. The Handbook of Research on Integrating Machine Learning Into HPC-Based Simulations and Analytics presents recent research efforts in designing and using ML techniques on HPC systems and discusses some of the results achieved thus far by cutting-edge relevant contributions. Covering topics such as data analytics, deep learning, and networking, this major reference work is ideal for computer scientists, academicians, engineers, researchers, scholars, practitioners, librarians, instructors, and students.
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