Neuromorphic Computing Principles and Organization

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Author :
Publisher : Springer Nature
ISBN 13 : 3030925250
Total Pages : 260 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Neuromorphic Computing Principles and Organization by : Abderazek Ben Abdallah

Download or read book Neuromorphic Computing Principles and Organization written by Abderazek Ben Abdallah and published by Springer Nature. This book was released on 2022-05-31 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for emerging AI applications. The book begins with an overview of neuromorphic computing systems and explores the fundamental concepts of artificial neural networks. Next, we discuss artificial neurons and how they have evolved in their representation of biological neuronal dynamics. Afterward, we discuss implementing these neural networks in neuron models, storage technologies, inter-neuron communication networks, learning, and various design approaches. Then, comes the fundamental design principle to build an efficient neuromorphic system in hardware. The challenges that need to be solved toward building a spiking neural network architecture with many synapses are discussed. Learning in neuromorphic computing systems and the major emerging memory technologies that promise neuromorphic computing are then given. A particular chapter of this book is dedicated to the circuits and architectures used for communication in neuromorphic systems. In particular, the Network-on-Chip fabric is introduced for receiving and transmitting spikes following the Address Event Representation (AER) protocol and the memory accessing method. In addition, the interconnect design principle is covered to help understand the overall concept of on-chip and off-chip communication. Advanced on-chip interconnect technologies, including si-photonic three-dimensional interconnects and fault-tolerant routing algorithms, are also given. The book also covers the main threats of reliability and discusses several recovery methods for multicore neuromorphic systems. This is important for reliable processing in several embedded neuromorphic applications. A reconfigurable design approach that supports multiple target applications via dynamic reconfigurability, network topology independence, and network expandability is also described in the subsequent chapters. The book ends with a case study about a real hardware-software design of a reliable three-dimensional digital neuromorphic processor geared explicitly toward the 3D-ICs biological brain’s three-dimensional structure. The platform enables high integration density and slight spike delay of spiking networks and features a scalable design. We present methods for fault detection and recovery in a neuromorphic system as well. Neuromorphic Computing Principles and Organization is an excellent resource for researchers, scientists, graduate students, and hardware-software engineers dealing with the ever-increasing demands on fault-tolerance, scalability, and low power consumption. It is also an excellent resource for teaching advanced undergraduate and graduate students about the fundamentals concepts, organization, and actual hardware-software design of reliable neuromorphic systems with learning and fault-tolerance capabilities.

Neuromorphic Engineering

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Author :
Publisher : CRC Press
ISBN 13 : 1000421325
Total Pages : 242 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Neuromorphic Engineering by : Elishai Ezra Tsur

Download or read book Neuromorphic Engineering written by Elishai Ezra Tsur and published by CRC Press. This book was released on 2021-08-27 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The brain is not a glorified digital computer. It does not store information in registers, and it does not mathematically transform mental representations to establish perception or behavior. The brain cannot be downloaded to a computer to provide immortality, nor can it destroy the world by having its emerged consciousness traveling in cyberspace. However, studying the brain's core computation architecture can inspire scientists, computer architects, and algorithm designers to think fundamentally differently about their craft. Neuromorphic engineers have the ultimate goal of realizing machines with some aspects of cognitive intelligence. They aspire to design computing architectures that could surpass existing digital von Neumann-based computing architectures' performance. In that sense, brain research bears the promise of a new computing paradigm. As part of a complete cognitive hardware and software ecosystem, neuromorphic engineering opens new frontiers for neuro-robotics, artificial intelligence, and supercomputing applications. This book will present neuromorphic engineering from three perspectives: the scientist, the computer architect, and the algorithm designer. We will zoom in and out of the different disciplines, allowing readers with diverse backgrounds to understand and appreciate the field. Overall, the book will cover the basics of neuronal modeling, neuromorphic circuits, neural architectures, event-based communication, and the neural engineering framework. Readers will have the opportunity to understand the different views over the inherently multidisciplinary field of neuromorphic engineering.

Event-Based Neuromorphic Systems

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 0470018496
Total Pages : 440 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Event-Based Neuromorphic Systems by : Shih-Chii Liu

Download or read book Event-Based Neuromorphic Systems written by Shih-Chii Liu and published by John Wiley & Sons. This book was released on 2015-02-16 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities. This cross-disciplinary text establishes how circuit building blocks are combined in architectures to construct complete systems. These include vision and auditory sensors as well as neuronal processing and learning circuits that implement models of nervous systems. Techniques for building multi-chip scalable systems are considered throughout the book, including methods for dealing with transistor mismatch, extensive discussions of communication and interfacing, and making systems that operate in the real world. The book also provides historical context that helps relate the architectures and circuits to each other and that guides readers to the extensive literature. Chapters are written by founding experts and have been extensively edited for overall coherence. This pioneering text is an indispensable resource for practicing neuromorphic electronic engineers, advanced electrical engineering and computer science students and researchers interested in neuromorphic systems. Key features: Summarises the latest design approaches, applications, and future challenges in the field of neuromorphic engineering. Presents examples of practical applications of neuromorphic design principles. Covers address-event communication, retinas, cochleas, locomotion, learning theory, neurons, synapses, floating gate circuits, hardware and software infrastructure, algorithms, and future challenges.

Neuromorphic Photonics

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Publisher : CRC Press
ISBN 13 : 1498725244
Total Pages : 412 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Neuromorphic Photonics by : Paul R. Prucnal

Download or read book Neuromorphic Photonics written by Paul R. Prucnal and published by CRC Press. This book was released on 2017-05-08 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.

Neuromorphic Devices for Brain-inspired Computing

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 3527349790
Total Pages : 258 pages
Book Rating : 4.5/5 (273 download)

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Book Synopsis Neuromorphic Devices for Brain-inspired Computing by : Qing Wan

Download or read book Neuromorphic Devices for Brain-inspired Computing written by Qing Wan and published by John Wiley & Sons. This book was released on 2022-05-16 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.

Neuromorphic Computing Systems for Industry 4.0

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Author :
Publisher : IGI Global
ISBN 13 : 1668465981
Total Pages : 400 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Neuromorphic Computing Systems for Industry 4.0 by : Dhanasekar, S.

Download or read book Neuromorphic Computing Systems for Industry 4.0 written by Dhanasekar, S. and published by IGI Global. This book was released on 2023-07-19 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: As artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today’s companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application. Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians.

Neuromorphic Computing

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Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1803561432
Total Pages : 298 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Neuromorphic Computing by :

Download or read book Neuromorphic Computing written by and published by BoD – Books on Demand. This book was released on 2023-11-15 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the cutting-edge world of Neuromorphic Computing, a groundbreaking volume that unravels the secrets of brain-inspired computational paradigms. Spanning neuroscience, artificial intelligence, and hardware design, this book presents a comprehensive exploration of neuromorphic systems, empowering both experts and newcomers to embrace the limitless potential of brain-inspired computing. Discover the fundamental principles that underpin neural computation as we journey through the origins of neuromorphic architectures, meticulously crafted to mimic the brain’s intricate neural networks. Unlock the true essence of learning mechanisms – unsupervised, supervised, and reinforcement learning – and witness how these innovations are shaping the future of artificial intelligence.

Thinking Machines

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Publisher : Academic Press
ISBN 13 : 0128182806
Total Pages : 324 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Thinking Machines by : Shigeyuki Takano

Download or read book Thinking Machines written by Shigeyuki Takano and published by Academic Press. This book was released on 2021-03-27 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks. This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning. Presents a clear understanding of various available machine learning hardware accelerator solutions that can be applied to selected machine learning algorithms Offers key insights into the development of hardware, from algorithms, software, logic circuits, to hardware accelerators Introduces the baseline characteristics of deep neural network models that should be treated by hardware as well Presents readers with a thorough review of past research and products, explaining how to design through ASIC and FPGA approaches for target machine learning models Surveys current trends and models in neuromorphic computing and neural network hardware architectures Outlines the strategy for advanced hardware development through the example of deep learning accelerators

Neuromorphic Cognitive Systems

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Author :
Publisher : Springer
ISBN 13 : 3319553100
Total Pages : 172 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Neuromorphic Cognitive Systems by : Qiang Yu

Download or read book Neuromorphic Cognitive Systems written by Qiang Yu and published by Springer. This book was released on 2017-05-03 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed. The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

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Author :
Publisher : MDPI
ISBN 13 : 3039285769
Total Pages : 244 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Memristors for Neuromorphic Circuits and Artificial Intelligence Applications by : Jordi Suñé

Download or read book Memristors for Neuromorphic Circuits and Artificial Intelligence Applications written by Jordi Suñé and published by MDPI. This book was released on 2020-04-09 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.

Primer to Neuromorphic Computing

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Author :
Publisher : Academic Press
ISBN 13 : 9780443214806
Total Pages : 0 pages
Book Rating : 4.2/5 (148 download)

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Book Synopsis Primer to Neuromorphic Computing by : Harish Garg

Download or read book Primer to Neuromorphic Computing written by Harish Garg and published by Academic Press. This book was released on 2024-09-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture. Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains.

Atomic Switch

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Publisher : Springer Nature
ISBN 13 : 303034875X
Total Pages : 270 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Atomic Switch by : Masakazu Aono

Download or read book Atomic Switch written by Masakazu Aono and published by Springer Nature. This book was released on 2020-03-02 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by the inventors and leading experts of this new field, the book results from the International Symposium on “Atomic Switch: Invention, Practical use and Future Prospects” which took place in Tsukuba, Japan on March 27th - 28th, 2017. The book chapters cover the different trends from the science and technology of atomic switches to their applications like brain-type information processing, artificial intelligence (AI) and completely novel functional electronic nanodevices. The current practical uses of the atomic switch are also described. As compared with the conventional semiconductor transistor switch, the atomic switch is more compact (~1/10) with much lower power consumption (~1/10) and scarcely influenced by strong electromagnetic noise and radiation including cosmic rays in space (~1/100). As such, this book is of interest to researchers, scholars and students willing to explore new materials, to refine the nanofabrication methods and to explore new and efficient device architectures.

Resistive Switching

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Publisher : John Wiley & Sons
ISBN 13 : 3527680934
Total Pages : 784 pages
Book Rating : 4.5/5 (276 download)

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Book Synopsis Resistive Switching by : Daniele Ielmini

Download or read book Resistive Switching written by Daniele Ielmini and published by John Wiley & Sons. This book was released on 2015-12-23 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its comprehensive coverage, this reference introduces readers to the wide topic of resistance switching, providing the knowledge, tools, and methods needed to understand, characterize and apply resistive switching memories. Starting with those materials that display resistive switching behavior, the book explains the basics of resistive switching as well as switching mechanisms and models. An in-depth discussion of memory reliability is followed by chapters on memory cell structures and architectures, while a section on logic gates rounds off the text. An invaluable self-contained book for materials scientists, electrical engineers and physicists dealing with memory research and development.

Advances in Memristor Neural Networks

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Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1789841151
Total Pages : 126 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Advances in Memristor Neural Networks by : Calin Ciufudean

Download or read book Advances in Memristor Neural Networks written by Calin Ciufudean and published by BoD – Books on Demand. This book was released on 2018-10-03 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, scientific research deals with alternative solutions for creating non-traditional computing systems, such as neural network architectures where the stochastic nature and live dynamics of memristive models play a key role. The features of memristors make it possible to direct processing and analysis of both biosystems and systems driven by artificial intelligence, as well as develop plausible physical models of spiking neural networks with self-organization. This book deals with advanced applications illustrating these concepts, and delivers an important contribution for the achievement of the next generation of intelligent hybrid biostructures. Different modeling and simulation tools can deliver an alternative to funding the theoretical approach as well as practical implementation of memristive systems.

Neural Engineering

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Publisher : MIT Press
ISBN 13 : 9780262550604
Total Pages : 384 pages
Book Rating : 4.5/5 (56 download)

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Book Synopsis Neural Engineering by : Chris Eliasmith

Download or read book Neural Engineering written by Chris Eliasmith and published by MIT Press. This book was released on 2003 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.

SpiNNaker - A Spiking Neural Network Architecture

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Author :
Publisher : NowOpen
ISBN 13 : 9781680836523
Total Pages : 352 pages
Book Rating : 4.8/5 (365 download)

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Book Synopsis SpiNNaker - A Spiking Neural Network Architecture by : Steve Furber

Download or read book SpiNNaker - A Spiking Neural Network Architecture written by Steve Furber and published by NowOpen. This book was released on 2020-03-15 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This books tells the story of the origins of the world's largest neuromorphic computing platform, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over

Efficient Processing of Deep Neural Networks

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Publisher : Springer Nature
ISBN 13 : 3031017668
Total Pages : 254 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Efficient Processing of Deep Neural Networks by : Vivienne Sze

Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.