Integrating Machine Learning into Hpc-based Simulations and Analytics

Youssef, Belgacem Ben (EDT); Ben Ismail, Mohamed Maher (EDT)

ISBN 10: 1668437953 / ISBN 13: 9781668437957

Edité par Engineering Science Reference, 2024

A propos de cet article

N° de réf. du vendeur 43998618-n

Détails bibliographiques

• Titre: Integrating Machine Learning into Hpc-based Simulations and Analytics
• Éditeur: Engineering Science Reference
• Date de parution: 2024
• Langue: anglais
• ISBN à 10 chiffres: 1668437953
• ISBN à 13 chiffres: 9781668437957
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

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.