Integrating Machine Learning Into HPC-Based Simulations and Analytics
Author | : Ben Youssef, Belgacem |
Publisher | : IGI Global |
Total Pages | : 540 |
Release | : 2024-12-13 |
ISBN-10 | : 9781668437964 |
ISBN-13 | : 1668437961 |
Rating | : 4/5 (64 Downloads) |
Download or read book Integrating Machine Learning Into HPC-Based Simulations and Analytics written by Ben Youssef, Belgacem and published by IGI Global. This book was released on 2024-12-13 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.