Hardcover. Researchers are working together to build intelligent systems that exploit a variety of real datasets using ML techniques to address problems and challenges in diverse research fields. More collaboration between the HPC and ML communities is encouraged for rapid and seamless progress toward an ecosystem that effectively serves both of these communities. As the performance improvements provided by semiconductor scaling diminish, future HPC systems are expected to exhibit an increased level of heterogeneity. These systems need to be flexible and provide low latency at all levels to effectively support new use cases and paradigms. Further, new tools and benchmarks are required to overcome the common challenges across HPC and ML applications. New programming tools, languages, compilers, and operating and runtime systems may also be needed to provide new abstractions, capabilities, and services. This book presents to the reader recent research efforts in designing and using ML techniques on HPC systems, discusses some of the results achieved thus far by cutting-edge contributions, as well as highlights some of the ongoing research works in these two fields. Another objective is to identify research challenges and opportunities in the area spanning the intersection of HPC and ML. It is ideal for students, academics, researchers, computer scientists, computer and electrical engineers, as well as experts in the field of machine learning and high-performance computing. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Detalles bibliogr�ficos

T�tulo: Handbook of Research on Integrating Machine Learning Into HPC-Based Simulations and Analytics (Hardcover)
Editor: IGI Global, Hershey
Fecha de publicaci�n: 2024
Idioma: Ingl�s
ISBN 10: 1668437953
ISBN 13: 9781668437957
Encuadernaci�n: Hardcover
Estado: new

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Sinopsis

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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