In-/Near-Memory Computing PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download In-/Near-Memory Computing PDF full book. Access full book title In-/Near-Memory Computing by Daichi Fujiki. Download full books in PDF and EPUB format.

In-/Near-Memory Computing

In-/Near-Memory Computing PDF Author: Daichi Fujiki
Publisher: Springer Nature
ISBN: 3031017722
Category : Technology & Engineering
Languages : en
Pages : 124

Get Book

Book Description
This book provides a structured introduction of the key concepts and techniques that enable in-/near-memory computing. For decades, processing-in-memory or near-memory computing has been attracting growing interest due to its potential to break the memory wall. Near-memory computing moves compute logic near the memory, and thereby reduces data movement. Recent work has also shown that certain memories can morph themselves into compute units by exploiting the physical properties of the memory cells, enabling in-situ computing in the memory array. While in- and near-memory computing can circumvent overheads related to data movement, it comes at the cost of restricted flexibility of data representation and computation, design challenges of compute capable memories, and difficulty in system and software integration. Therefore, wide deployment of in-/near-memory computing cannot be accomplished without techniques that enable efficient mapping of data-intensive applications to such devices, without sacrificing accuracy or increasing hardware costs excessively. This book describes various memory substrates amenable to in- and near-memory computing, architectural approaches for designing efficient and reliable computing devices, and opportunities for in-/near-memory acceleration of different classes of applications.

In-/Near-Memory Computing

In-/Near-Memory Computing PDF Author: Daichi Fujiki
Publisher: Springer Nature
ISBN: 3031017722
Category : Technology & Engineering
Languages : en
Pages : 124

View

Book Description
This book provides a structured introduction of the key concepts and techniques that enable in-/near-memory computing. For decades, processing-in-memory or near-memory computing has been attracting growing interest due to its potential to break the memory wall. Near-memory computing moves compute logic near the memory, and thereby reduces data movement. Recent work has also shown that certain memories can morph themselves into compute units by exploiting the physical properties of the memory cells, enabling in-situ computing in the memory array. While in- and near-memory computing can circumvent overheads related to data movement, it comes at the cost of restricted flexibility of data representation and computation, design challenges of compute capable memories, and difficulty in system and software integration. Therefore, wide deployment of in-/near-memory computing cannot be accomplished without techniques that enable efficient mapping of data-intensive applications to such devices, without sacrificing accuracy or increasing hardware costs excessively. This book describes various memory substrates amenable to in- and near-memory computing, architectural approaches for designing efficient and reliable computing devices, and opportunities for in-/near-memory acceleration of different classes of applications.

In-/Near-Memory Computing

In-/Near-Memory Computing PDF Author: Daichi Fujiki
Publisher: Morgan & Claypool Publishers
ISBN: 1636391877
Category : Computers
Languages : en
Pages : 142

View

Book Description
This book provides a structured introduction of the key concepts and techniques that enable in-/near-memory computing. For decades, processing-in-memory or near-memory computing has been attracting growing interest due to its potential to break the memory wall. Near-memory computing moves compute logic near the memory, and thereby reduces data movement. Recent work has also shown that certain memories can morph themselves into compute units by exploiting the physical properties of the memory cells, enabling in-situ computing in the memory array. While in- and near-memory computing can circumvent overheads related to data movement, it comes at the cost of restricted flexibility of data representation and computation, design challenges of compute capable memories, and difficulty in system and software integration. Therefore, wide deployment of in-/near-memory computing cannot be accomplished without techniques that enable efficient mapping of data-intensive applications to such devices, without sacrificing accuracy or increasing hardware costs excessively. This book describes various memory substrates amenable to in- and near-memory computing, architectural approaches for designing efficient and reliable computing devices, and opportunities for in-/near-memory acceleration of different classes of applications.

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

Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design PDF Author: Nan Zheng
Publisher: John Wiley & Sons
ISBN: 1119507383
Category : Computers
Languages : en
Pages : 296

View

Book Description
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.

Architecture of Computing Systems – ARCS 2020

Architecture of Computing Systems – ARCS 2020 PDF Author: André Brinkmann
Publisher: Springer Nature
ISBN: 3030527948
Category : Computers
Languages : en
Pages : 257

View

Book Description
This book constitutes the proceedings of the 33rd International Conference on Architecture of Computing Systems, ARCS 2020, held in Aachen, Germany, in May 2020.* The 12 full papers in this volume were carefully reviewed and selected from 33 submissions. 6 workshop papers are also included. ARCS has always been a conference attracting leading-edge research outcomes in Computer Architecture and Operating Systems, including a wide spectrum of topics ranging from embedded and real-time systems all the way to large-scale and parallel systems. The selected papers focus on concepts and tools for incorporating self-adaptation and self-organization mechanisms in high-performance computing systems. This includes upcoming approaches for runtime modifications at various abstraction levels, ranging from hardware changes to goal changes and their impact on architectures, technologies, and languages. *The conference was canceled due to the COVID-19 pandemic.

Handbook of Memristor Networks

Handbook of Memristor Networks PDF Author: Leon Chua
Publisher: Springer Nature
ISBN: 331976375X
Category : Computers
Languages : en
Pages : 1368

View

Book Description
This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware. With contributions from leaders in computer science, mathematics, electronics, physics, material science and engineering, the book offers an indispensable source of information and an inspiring reference text for future generations of computer scientists, mathematicians, physicists, material scientists and engineers working in this dynamic field.

Near Threshold Computing

Near Threshold Computing PDF Author: Michael Hübner
Publisher: Springer
ISBN: 3319233890
Category : Technology & Engineering
Languages : en
Pages : 100

View

Book Description
This book explores near-threshold computing (NTC), a design-space using techniques to run digital chips (processors) near the lowest possible voltage. Readers will be enabled with specific techniques to design chips that are extremely robust; tolerating variability and resilient against errors. Variability-aware voltage and frequency allocation schemes will be presented that will provide performance guarantees, when moving toward near-threshold manycore chips. · Provides an introduction to near-threshold computing, enabling reader with a variety of tools to face the challenges of the power/utilization wall; · Demonstrates how to design efficient voltage regulation, so that each region of the chip can operate at the most efficient voltage and frequency point; · Investigates how performance guarantees can be ensured when moving towards NTC manycores through variability-aware voltage and frequency allocation schemes.

Emerging Memory and Computing Devices in the Era of Intelligent Machines

Emerging Memory and Computing Devices in the Era of Intelligent Machines PDF Author: Pedram Khalili Amiri
Publisher: MDPI
ISBN: 3039285025
Category : Technology & Engineering
Languages : en
Pages : 276

View

Book Description
Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system. This is driven by the requirements of data-intensive applications in artificial intelligence, autonomous systems, and edge computing. We are at an exciting time in the semiconductor industry where several innovative device and technology concepts are being developed to respond to these demands, and capture shares of the fast growing market for AI-related hardware. This special issue is devoted to highlighting, discussing and presenting the latest advancements in this area, drawing on the best work on emerging memory devices including magnetic, resistive, phase change, and other types of memory. The special issue is interested in work that presents concepts, ideas, and recent progress ranging from materials, to memory devices, physics of switching mechanisms, circuits, and system applications, as well as progress in modeling and design tools. Contributions that bridge across several of these layers are especially encouraged.

Multi-Processor System-on-Chip 1

Multi-Processor System-on-Chip 1 PDF Author: Liliana Andrade
Publisher: John Wiley & Sons
ISBN: 1119818281
Category : Computers
Languages : en
Pages : 320

View

Book Description
A Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory, communication devices and computing units. This book, presented in two volumes – Architectures and Applications – therefore celebrates the 20th anniversary of MPSoC, an interdisciplinary forum that focuses on multi-core and multi-processor hardware and software systems. It is this interdisciplinarity which has led to MPSoC bringing together experts in these fields from around the world, over the last two decades. Multi-Processor System-on-Chip 1 covers the key components of MPSoC: processors, memory, interconnect and interfaces. It describes advance features of these components and technologies to build efficient MPSoC architectures. All the main components are detailed: use of memory and their technology, communication support and consistency, and specific processor architectures for general purposes or for dedicated applications.

Emerging Computing Techniques in Engineering

Emerging Computing Techniques in Engineering PDF Author: Matthew N. O. Sadiku
Publisher: AuthorHouse
ISBN: 1665569166
Category : Education
Languages : en
Pages : 409

View

Book Description
The book is divided into three volumes to cover all computing topics. This is the first volume and it has 23 chapters. It focuses on general computing techniques such as cloud computing, grid computing, pervasive computing, optical computing, web computing, parallel computing, distributed computing, high-performance computing, GPU computing, exascale & extreme computing, in-memory computing, embedded computing, quantum computing, and green computing

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications PDF Author: Christos Volos
Publisher: Academic Press
ISBN: 0128232021
Category : Architecture
Languages : en
Pages : 568

View

Book Description
Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields. Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence