In Memory Computing Hardware Accelerators For Data Intensive Applications
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In Memory Computing Hardware Accelerators For Data Intensive Applications
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Author : Baker Mohammad
language : en
Publisher: Springer Nature
Release Date : 2023-09-25
In Memory Computing Hardware Accelerators For Data Intensive Applications written by Baker Mohammad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-25 with Technology & Engineering categories.
This book describes the state-of-the-art of technology and research on In-Memory Computing Hardware Accelerators for Data-Intensive Applications. The authors discuss how processing-centric computing has become insufficient to meet target requirements and how Memory-centric computing may be better suited for the needs of current applications. This reveals for readers how current and emerging memory technologies are causing a shift in the computing paradigm. The authors do deep-dive discussions on volatile and non-volatile memory technologies, covering their basic memory cell structures, operations, different computational memory designs and the challenges associated with them. Specific case studies and potential applications are provided along with their current status and commercial availability in the market.
Recent Advances In Neuromorphic Computing
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Author :
language : en
Publisher: BoD – Books on Demand
Release Date : 2025-07-02
Recent Advances In Neuromorphic Computing written by and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-02 with Computers categories.
Artificial Intelligence (AI) is a transformative technology that reshapes our daily lives. Machine Learning (ML), the engine of such a revolution, empowers computers to learn from data, driving innovation in areas such as medicine, robotics, and smart cities through edge applications. These applications bring AI processing closer to the data source, enabling real-time insights and decisions. This evolution is fueled by advancements in hardware and architecture: (1) neuromorphic computing promises unparalleled efficiency; (2) in-memory computing eliminates data access bottlenecks, while emerging memory materials offer denser, faster, and more energy-efficient storage. Looking ahead, AI promises even more profound changes. For instance, explainable AI will make decision-making more transparent, and truly autonomous systems will adapt to unforeseen circumstances. Last but not least, the convergence of AI with quantum computing could unlock entirely new possibilities. This journey showcases a deep understanding of both the theoretical foundations and practical applications of AI. It also demands careful consideration of ethical implications and a commitment to responsible development, ensuring that AI benefits all of humanity.
Data Intensive Computing
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Author : Ian Gorton
language : en
Publisher: Cambridge University Press
Release Date : 2013
Data Intensive Computing written by Ian Gorton and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.
Describes principles of the emerging field of data-intensive computing, along with methods for designing, managing and analyzing the big data sets of today.
Emerging Technology And Architecture For Big Data Analytics
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Author : Anupam Chattopadhyay
language : en
Publisher: Springer
Release Date : 2017-04-19
Emerging Technology And Architecture For Big Data Analytics written by Anupam Chattopadhyay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-19 with Technology & Engineering categories.
This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities. Provides a single-source reference to hardware architectures for big-data analytics; Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems; Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics.
Computing With Memory For Energy Efficient Robust Systems
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Author : Somnath Paul
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-09-07
Computing With Memory For Energy Efficient Robust Systems written by Somnath Paul and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-07 with Technology & Engineering categories.
This book analyzes energy and reliability as major challenges faced by designers of computing frameworks in the nanometer technology regime. The authors describe the existing solutions to address these challenges and then reveal a new reconfigurable computing platform, which leverages high-density nanoscale memory for both data storage and computation to maximize the energy-efficiency and reliability. The energy and reliability benefits of this new paradigm are illustrated and the design challenges are discussed. Various hardware and software aspects of this exciting computing paradigm are described, particularly with respect to hardware-software co-designed frameworks, where the hardware unit can be reconfigured to mimic diverse application behavior. Finally, the energy-efficiency of the paradigm described is compared with other, well-known reconfigurable computing platforms.
Artificial Intelligence And Hardware Accelerators
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Author : Ashutosh Mishra
language : en
Publisher: Springer Nature
Release Date : 2023-03-15
Artificial Intelligence And Hardware Accelerators written by Ashutosh Mishra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-15 with Technology & Engineering categories.
This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their computational requirements, along with the multifaceted applications. Coverage focuses broadly on the hardware aspects of training, inference, mobile devices, and autonomous vehicles (AVs) based AI accelerators
Embedded Computing For High Performance
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Author : João Manuel Paiva Cardoso
language : en
Publisher: Morgan Kaufmann
Release Date : 2017-06-13
Embedded Computing For High Performance written by João Manuel Paiva Cardoso and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-13 with Computers categories.
Embedded Computing for High Performance: Design Exploration and Customization Using High-level Compilation and Synthesis Tools provides a set of real-life example implementations that migrate traditional desktop systems to embedded systems. Working with popular hardware, including Xilinx and ARM, the book offers a comprehensive description of techniques for mapping computations expressed in programming languages such as C or MATLAB to high-performance embedded architectures consisting of multiple CPUs, GPUs, and reconfigurable hardware (FPGAs). The authors demonstrate a domain-specific language (LARA) that facilitates retargeting to multiple computing systems using the same source code. In this way, users can decouple original application code from transformed code and enhance productivity and program portability. After reading this book, engineers will understand the processes, methodologies, and best practices needed for the development of applications for high-performance embedded computing systems. - Focuses on maximizing performance while managing energy consumption in embedded systems - Explains how to retarget code for heterogeneous systems with GPUs and FPGAs - Demonstrates a domain-specific language that facilitates migrating and retargeting existing applications to modern systems - Includes downloadable slides, tools, and tutorials
Advances In Memristors Memristive Devices And Systems
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Author : Sundarapandian Vaidyanathan
language : en
Publisher: Springer
Release Date : 2017-02-15
Advances In Memristors Memristive Devices And Systems written by Sundarapandian Vaidyanathan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-15 with Technology & Engineering categories.
This book reports on the latest advances in and applications of memristors, memristive devices and systems. It gathers 20 contributed chapters by subject experts, including pioneers in the field such as Leon Chua (UC Berkeley, USA) and R.S. Williams (HP Labs, USA), who are specialized in the various topics addressed in this book, and covers broad areas of memristors and memristive devices such as: memristor emulators, oscillators, chaotic and hyperchaotic memristive systems, control of memristive systems, memristor-based min-max circuits, canonic memristors, memristive-based neuromorphic applications, implementation of memristor-based chaotic oscillators, inverse memristors, linear memristor devices, delayed memristive systems, flux-controlled memristive emulators, etc. Throughout the book, special emphasis is given to papers offering practical solutions and design, modeling, and implementation insights to address current research problems in memristors, memristive devices and systems. As such, it offers a valuable reference book on memristors and memristive devices for graduate students and researchers with a basic knowledge of electrical and control systems engineering.
Research Infrastructures For Hardware Accelerators
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Author : Yakun Sophia Shao
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2015-11-01
Research Infrastructures For Hardware Accelerators written by Yakun Sophia Shao and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-01 with Computers categories.
Hardware acceleration in the form of customized datapath and control circuitry tuned to specific applications has gained popularity for its promise to utilize transistors more efficiently. Historically, the computer architecture community has focused on general-purpose processors, and extensive research infrastructure has been developed to support research efforts in this domain. Envisioning future computing systems with a diverse set of general-purpose cores and accelerators, computer architects must add accelerator-related research infrastructures to their toolboxes to explore future heterogeneous systems. This book serves as a primer for the field, as an overview of the vast literature on accelerator architectures and their design flows, and as a resource guidebook for researchers working in related areas.
Building Scalable Data Intensive Applications
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Author : Chandani Kaul
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Building Scalable Data Intensive Applications written by Chandani Kaul and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Building Scalable Data-Intensive Applications explores the vast landscape of digital data from social networks, blogs, business, science, and engineering. This book delves into data-intensive computing, which is essential for understanding and processing massive amounts of data. Utilizing the latest software, algorithms, and hardware, data-intensive applications deliver timely and meaningful insights, addressing the challenges posed by exponentially growing data complexity. We provide a comprehensive reference for computing professionals and researchers, covering the field's scope, key challenges, and state-of-the-art approaches required for future data-intensive problems. Our chapters include general principles and methods for designing and managing systems that analyze vast datasets, particularly those stored in the cloud. Additionally, we explore practical applications in cybersecurity and bioinformatics to illustrate these principles in action. Building Scalable Data-Intensive Applications is an invaluable resource for anyone looking to navigate and harness the power of data-intensive computing.