Neural Hardware

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Efficient Processing of Deep Neural Networks

Author : Vivienne Sze
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.

Hardware Architectures for Deep Learning

Author : Masoud Daneshtalab
Publisher : Institution of Engineering and Technology
ISBN 13 : 1785617680
Total Pages : 329 pages
Book Rating : 4.7/5 (856 download)

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Book Synopsis Hardware Architectures for Deep Learning by : Masoud Daneshtalab

Download or read book Hardware Architectures for Deep Learning written by Masoud Daneshtalab and published by Institution of Engineering and Technology. This book was released on 2020-02-28 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents and discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks.

Neural Networks

Author : Berndt Müller
Publisher : Springer Science & Business Media
ISBN 13 : 3642577601
Total Pages : 340 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Neural Networks by : Berndt Müller

Download or read book Neural Networks written by Berndt Müller and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.

Ferroelectrics

Author : Mickaël Lallart
Publisher : BoD – Books on Demand
ISBN 13 : 9533074566
Total Pages : 266 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis Ferroelectrics by : Mickaël Lallart

Download or read book Ferroelectrics written by Mickaël Lallart and published by BoD – Books on Demand. This book was released on 2011-08-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ferroelectric materials have been and still are widely used in many applications, that have moved from sonar towards breakthrough technologies such as memories or optical devices. This book is a part of a four volume collection (covering material aspects, physical effects, characterization and modeling, and applications) and focuses on the application of ferroelectric devices to innovative systems. In particular, the use of these materials as varying capacitors, gyroscope, acoustics sensors and actuators, microgenerators and memory devices will be exposed, providing an up-to-date review of recent scientific findings and recent advances in the field of ferroelectric devices.

Artificial Intelligence Hardware Design

Author : Albert Chun-Chen Liu
Publisher : John Wiley & Sons
ISBN 13 : 1119810477
Total Pages : 244 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Artificial Intelligence Hardware Design by : Albert Chun-Chen Liu

Download or read book Artificial Intelligence Hardware Design written by Albert Chun-Chen Liu and published by John Wiley & Sons. This book was released on 2021-08-23 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE HARDWARE DESIGN Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field In Artificial Intelligence Hardware Design: Challenges and Solutions, distinguished researchers and authors Drs. Albert Chun Chen Liu and Oscar Ming Kin Law deliver a rigorous and practical treatment of the design applications of specific circuits and systems for accelerating neural network processing. Beginning with a discussion and explanation of neural networks and their developmental history, the book goes on to describe parallel architectures, streaming graphs for massive parallel computation, and convolution optimization. The authors offer readers an illustration of in-memory computation through Georgia Tech’s Neurocube and Stanford’s Tetris accelerator using the Hybrid Memory Cube, as well as near-memory architecture through the embedded eDRAM of the Institute of Computing Technology, the Chinese Academy of Science, and other institutions. Readers will also find a discussion of 3D neural processing techniques to support multiple layer neural networks, as well as information like: A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU An examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition Perfect for hardware and software engineers and firmware developers, Artificial Intelligence Hardware Design is an indispensable resource for anyone working with Neural Processing Units in either a hardware or software capacity.

Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design

Author : Nan Zheng
Publisher : John Wiley & Sons
ISBN 13 : 1119507391
Total Pages : 300 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design by : Nan Zheng

Download or read book Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design written by Nan Zheng and published by John Wiley & Sons. This book was released on 2019-10-18 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities—and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks. The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware. Includes cross-layer survey of hardware accelerators for neuromorphic algorithms Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.

Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices

Author : Manan Suri
Publisher : Springer
ISBN 13 : 813223703X
Total Pages : 217 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices by : Manan Suri

Download or read book Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices written by Manan Suri and published by Springer. This book was released on 2017-01-21 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.

Nature Inspired Robotics

Author : Jagjit Singh Dhatterwal
Publisher : CRC Press
ISBN 13 : 104008818X
Total Pages : 341 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Nature Inspired Robotics by : Jagjit Singh Dhatterwal

Download or read book Nature Inspired Robotics written by Jagjit Singh Dhatterwal and published by CRC Press. This book was released on 2024-07-24 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the theories and methods of Nature-Inspired Robotics in artificial intelligence. Software and hardware technologies, alongside theories and methods, illustrate the application of bio-inspired artificial intelligence. It includes discussions on topics such as Robot Control Manipulators, Geometric Transformation, Robotic Drive Systems and Nature Inspired Robotic Neural System. Elaborating upon recent progress made in five distinct configurations of nature-inspired computing, it explores the potential applications of this technology in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. · Discusses advances in cutting-edge technology in brain-inspired computing, perception technologies and aspects of neuromorphic electronics · Offers a thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms · Provides comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviours · Includes cognitive behaviour of Inspired Robotics and cognitive technologies with applications in Artificial Intelligence · Contains practical discussions of neuromorphic devices based on chalcogenide and organic materials. This text acts as a reference book for students, scholars, and industry professionals.

Is There a God?

Author : Graham Oppy
Publisher : Routledge
ISBN 13 : 1000456293
Total Pages : 376 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Is There a God? by : Graham Oppy

Download or read book Is There a God? written by Graham Oppy and published by Routledge. This book was released on 2021-10-12 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bertrand Russell famously quipped that he didn’t believe in God for the same reason that he didn’t believe in a teapot in orbit between the earth and Mars: it is a bizarre assertion for which no evidence can be provided. Is belief in God really like belief in Russell’s teapot? Kenneth L. Pearce argues that God is no teapot. God is a real answer to the deepest question of all: why is there something rather than nothing? Graham Oppy argues that we should believe that there are none but natural causal entities with none but natural causal properties—and hence should believe that there are no gods. Beginning from this basic disagreement, the authors proceed to discuss and debate a wide range of philosophical questions, including questions about explanation, necessity, rationality, religious experience, mathematical objects, the foundations of ethics, and the methodology of philosophy. Each author first presents his own side, and then they interact through two rounds of objections and replies. Pedagogical features include standard form arguments, section summaries, bolded key terms and principles, a glossary, and annotated reading lists. In the volume foreword, Helen De Cruz calls the debate "both edifying and a joy," and sums up what’s at stake: "Here you have two carefully formulated positive proposals for worldviews that explain all that is: classical theism, or naturalistic atheism. You can follow along with the authors and deliberate: which one do you find more plausible?" Though written with beginning students in mind, this debate will be of interest to philosophers at all levels and to anyone who values careful, rational thought about the nature of reality and our place in it.

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Author : Shiho Kim
Publisher : Elsevier
ISBN 13 : 0128231238
Total Pages : 414 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Hardware Accelerator Systems for Artificial Intelligence and Machine Learning by : Shiho Kim

Download or read book Hardware Accelerator Systems for Artificial Intelligence and Machine Learning written by Shiho Kim and published by Elsevier. This book was released on 2021-04-07 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. Updates on new information on the architecture of GPU, NPU and DNN Discusses In-memory computing, Machine intelligence and Quantum computing Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance

Contemporary Computing

Author : Sanjay Ranka
Publisher : Springer
ISBN 13 : 3642148255
Total Pages : 295 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Contemporary Computing by : Sanjay Ranka

Download or read book Contemporary Computing written by Sanjay Ranka and published by Springer. This book was released on 2010-08-12 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the second part of the refereed proceedings of the Third International Conference, IC3 2010, held in Noida, India, in August 2010. The 23 revised full papers presented were carefully reviewed and selected from numerous submissions.

Optical SuperComputing

Author : Shlomi Dolev
Publisher : Springer Science & Business Media
ISBN 13 : 3540856722
Total Pages : 135 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Optical SuperComputing by : Shlomi Dolev

Download or read book Optical SuperComputing written by Shlomi Dolev and published by Springer Science & Business Media. This book was released on 2008-08-12 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the The International Workshop on Optical SuperComputing, OSC 2008, held in Vienna, Austria, August 2008 in conjunction with the 7th International Conference on Unconventional Computation UC 2008. OCS is a new annual forum for research presentations on all facets of optical computing for solving hard computation tasks. Topics of interest include, but are not limited to: Design of optical computing devices, electrooptics devices for interacting with optical computing devices, practical implementations, analysis of existing devices and case studies, optical and laser switching technologies, applications and algorithms for optical devices, alpha practical, x-rays and nano-technologies for optical computing.

Handbook of Neural Computation

Author : Emile Fiesler
Publisher : CRC Press
ISBN 13 : 0429525605
Total Pages : 1129 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Handbook of Neural Computation by : Emile Fiesler

Download or read book Handbook of Neural Computation written by Emile Fiesler and published by CRC Press. This book was released on 2020-01-15 with total page 1129 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Neural Computation is a practical, hands-on guide to the design and implementation of neural networks used by scientists and engineers to tackle difficult and/or time-consuming problems. The handbook bridges an information pathway between scientists and engineers in different disciplines who apply neural networks to similar probl

Advances in GPU Research and Practice

Author : Hamid Sarbazi-Azad
Publisher : Morgan Kaufmann
ISBN 13 : 0128037881
Total Pages : 776 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Advances in GPU Research and Practice by : Hamid Sarbazi-Azad

Download or read book Advances in GPU Research and Practice written by Hamid Sarbazi-Azad and published by Morgan Kaufmann. This book was released on 2016-09-15 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in GPU Research and Practice focuses on research and practices in GPU based systems. The topics treated cover a range of issues, ranging from hardware and architectural issues, to high level issues, such as application systems, parallel programming, middleware, and power and energy issues. Divided into six parts, this edited volume provides the latest research on GPU computing. Part I: Architectural Solutions focuses on the architectural topics that improve on performance of GPUs, Part II: System Software discusses OS, compilers, libraries, programming environment, languages, and paradigms that are proposed and analyzed to help and support GPU programmers. Part III: Power and Reliability Issues covers different aspects of energy, power, and reliability concerns in GPUs. Part IV: Performance Analysis illustrates mathematical and analytical techniques to predict different performance metrics in GPUs. Part V: Algorithms presents how to design efficient algorithms and analyze their complexity for GPUs. Part VI: Applications and Related Topics provides use cases and examples of how GPUs are used across many sectors. - Discusses how to maximize power and obtain peak reliability when designing, building, and using GPUs - Covers system software (OS, compilers), programming environments, languages, and paradigms proposed to help and support GPU programmers - Explains how to use mathematical and analytical techniques to predict different performance metrics in GPUs - Illustrates the design of efficient GPU algorithms in areas such as bioinformatics, complex systems, social networks, and cryptography - Provides applications and use case scenarios in several different verticals, including medicine, social sciences, image processing, and telecommunications

Talking Nets

Author : James A. Anderson
Publisher : MIT Press
ISBN 13 : 9780262511117
Total Pages : 452 pages
Book Rating : 4.5/5 (111 download)

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Book Synopsis Talking Nets by : James A. Anderson

Download or read book Talking Nets written by James A. Anderson and published by MIT Press. This book was released on 2000-02-28 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surprising tales from the scientists who first learned how to use computers to understand the workings of the human brain. Since World War II, a group of scientists has been attempting to understand the human nervous system and to build computer systems that emulate the brain's abilities. Many of the early workers in this field of neural networks came from cybernetics; others came from neuroscience, physics, electrical engineering, mathematics, psychology, even economics. In this collection of interviews, those who helped to shape the field share their childhood memories, their influences, how they became interested in neural networks, and what they see as its future. The subjects tell stories that have been told, referred to, whispered about, and imagined throughout the history of the field. Together, the interviews form a Rashomon-like web of reality. Some of the mythic people responsible for the foundations of modern brain theory and cybernetics, such as Norbert Wiener, Warren McCulloch, and Frank Rosenblatt, appear prominently in the recollections. The interviewees agree about some things and disagree about more. Together, they tell the story of how science is actually done, including the false starts, and the Darwinian struggle for jobs, resources, and reputation. Although some of the interviews contain technical material, there is no actual mathematics in the book. Contributors James A. Anderson, Michael Arbib, Gail Carpenter, Leon Cooper, Jack Cowan, Walter Freeman, Stephen Grossberg, Robert Hecht-Neilsen, Geoffrey Hinton, Teuvo Kohonen, Bart Kosko, Jerome Lettvin, Carver Mead, David Rumelhart, Terry Sejnowski, Paul Werbos, Bernard Widrow

Micro- and Nanoelectronics

Author : Tomasz Brozek
Publisher : CRC Press
ISBN 13 : 1482214911
Total Pages : 383 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Micro- and Nanoelectronics by : Tomasz Brozek

Download or read book Micro- and Nanoelectronics written by Tomasz Brozek and published by CRC Press. This book was released on 2017-12-19 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Micro- and Nanoelectronics: Emerging Device Challenges and Solutions presents a comprehensive overview of the current state of the art of micro- and nanoelectronics, covering the field from fundamental science and material properties to novel ways of making nanodevices. Containing contributions from experts in both industry and academia, this cutting-edge text: Discusses emerging silicon devices for CMOS technologies, fully depleted device architectures, characteristics, and scaling Explains the specifics of silicon compound devices (SiGe, SiC) and their unique properties Explores various options for post-CMOS nanoelectronics, such as spintronic devices and nanoionic switches Describes the latest developments in carbon nanotubes, iii-v devices structures, and more Micro- and Nanoelectronics: Emerging Device Challenges and Solutions provides an excellent representation of a complex engineering field, examining emerging materials and device architecture alternatives with the potential to shape the future of nanotechnology.

An Introduction to Neural Networks

Author : James A. Anderson
Publisher : MIT Press
ISBN 13 : 9780262510813
Total Pages : 680 pages
Book Rating : 4.5/5 (18 download)

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Book Synopsis An Introduction to Neural Networks by : James A. Anderson

Download or read book An Introduction to Neural Networks written by James A. Anderson and published by MIT Press. This book was released on 1995 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author's own ideas. Students learn how to teach arithmetic to a neural network and get a short course on linear associative memory and adaptive maps. They are introduced to the author's brain-state-in-a-box (BSB) model and are provided with some of the neurobiological background necessary for a firm grasp of the general subject. The field now known as neural networks has split in recent years into two major groups, mirrored in the texts that are currently available: the engineers who are primarily interested in practical applications of the new adaptive, parallel computing technology, and the cognitive scientists and neuroscientists who are interested in scientific applications. As the gap between these two groups widens, Anderson notes that the academics have tended to drift off into irrelevant, often excessively abstract research while the engineers have lost contact with the source of ideas in the field. Neuroscience, he points out, provides a rich and valuable source of ideas about data representation and setting up the data representation is the major part of neural network programming. Both cognitive science and neuroscience give insights into how this can be done effectively: cognitive science suggests what to compute and neuroscience suggests how to compute it.