Fabrizio Lombardi – författare

This book explores the technological developments at various levels of abstraction, of the new paradigm of approximate computing. The authors describe in a single-source the state-of-the-art, covering the entire spectrum of research activities in approximate computing, bridging device, circuit, architecture, and system levels.  Content includes tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications developed in approximate computing for a wide scope of readership and specialists.Serves as a single-source reference to state-of-the-art of approximate computing;Covers broad range of topics, from circuits to applications;Includes contributions by leading researchers, from academia and industry.

This book explores the technological developments at various levels of abstraction, of the new paradigm of approximate computing. The authors describe in a single-source the state-of-the-art, covering the entire spectrum of research activities in approximate computing, bridging device, circuit, architecture, and system levels.  Content includes tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications developed in approximate computing for a wide scope of readership and specialists.Serves as a single-source reference to state-of-the-art of approximate computing;Covers broad range of topics, from circuits to applications;Includes contributions by leading researchers, from academia and industry.

This book explores the technological developments at various levels of abstraction, of the new paradigm of approximate computing. The authors describe in a single-source the state-of-the-art, covering the entire spectrum of research activities in approximate computing, bridging device, circuit, architecture, and system levels.  Content includes tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications developed in approximate computing for a wide scope of readership and specialists.Serves as a single-source reference to state-of-the-art of approximate computing;Covers broad range of topics, from circuits to applications;Includes contributions by leading researchers, from academia and industry.

This book provides a single-source reference to the state-of-the-art in emerging computer systems. The authors address the technological contributions and developments at various hardware levels of new systems that compute under novel operational paradigms such as stochastic, probabilistic/inexact, neuromorphic, spintronic, bio-inspired and in-memory computing. Coverage includes the entire stack, i.e., from circuit, architecture, up to system level. This book includes tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and a range of applications.

This book provides a single-source reference to the state-of-the-art in emerging computer systems. The authors address the technological contributions and developments at various hardware levels of new systems that compute under novel operational paradigms such as stochastic, probabilistic/inexact, neuromorphic, spintronic, bio-inspired and in-memory computing. Coverage includes the entire stack, i.e., from circuit, architecture, up to system level. This book includes tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and a range of applications.

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.

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.

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.