Integrating Machine Learning Into HPC-Based Simulations and Analytics

Belgacem Ben Youssef

ISBN 10: 1668437953 / ISBN 13: 9781668437957

Verlag: IGI Global, 2024

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - 'This edited book aims to present to the reader recent research efforts in designing and using ML techniques on HPC systems, discuss some of the results achieved thus far by cutting-edge relevant contributions. Another objective is to identify research challenges and opportunities in the area spanning the intersection of HPC and ML. In fact, further collaboration between the HPC and ML communities is encouraged for rapid and seamless progress toward an ecosystem that effectively serves both of these communities. Furthermore, new tools and benchmarks are required to overcome the common challenges across HPC and ML applications. The goals of this form of convergence are fourfold: 1. Obtain optimized solutions that show discernible reduction in compute requirements. 2. Facilitate having a more dynamic view of domain sciences. 3. Develop integrated knowledge through interdisciplinary collaboration. 4. Stimulate innovations with deep societal impact through the provisioning of new advances in scientific research spanning many application areas'.

Bestandsnummer des Verkäufers 9781668437957

Bibliografische Details

• Titel: Integrating Machine Learning Into HPC-Based Simulations and Analytics
• Verlag: IGI Global
• Erscheinungsjahr: 2024
• Sprache: Englisch
• ISBN-10: 1668437953
• ISBN-13: 9781668437957
• Einband: Buch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

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.