Machine Learning Systems

Springer, 2026

This book addresses the technological contributions and developments of advanced hardware for Machine Learning (ML) computing systems. The authors discuss state-of-the-art progress in this area (and related topics) as well as reporting on their application to diverse fields. This is achieved by chapters covering the entire spectrum of research activities to include design and applications, with a focus on high performance and dependable operation. The entire hardware stack (from circuit, to architecture, up to the system level) is discussed in detail. The book will cover innovative material as well as tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications over a wide spectrum of scope for an enlarged readership, so to include engineers as well as scientists. Discusses a wide range of topics for Machine Learning-based computer systems; Covers design and application for the entire hardware stack, with a focus on high performance and dependability; Includes innovative material, as well as tutorials, reviews and surveys of current theoretical/experimental results.

• Curatore: Zhen Gao, Shanshan Liu, Fabrizio Lombardi, Pedro Reviriego
• Anno edizione: 2026
• Editore: Springer
• Formato: EPUB3 con Adobe DRM
• Lingua: Inglese
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9783032179487