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Herausgeber: 
  • Belgacem Ben Youssef
  • Mohamed Maher Ben Ismail
  • Integrating Machine Learning Into HPC-Based Simulations and Analytics 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Dezember 2024  
    Genre:  Ratgeber 
     
    Analytics / Data Analytics / Deep Learning / high-performance computing systems / machine learning / Networking / Parallelization / Simulations
    ISBN:  9798337316864 
    EAN-Code: 
    9798337316864 
    Verlag:  IGI Global 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 280 mm / B 216 mm / D 29 mm 
    Gewicht:  1342 gr 
    Seiten:  540 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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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