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This book serves as a single-source reference to the latest advances in Approximate Computing (AxC), a promising technique for increasing performance or reducing the cost and power consumption of a computing system. The authors discuss the different AxC design and validation techniques, and their integration. They also describe real AxC applications, spanning from mobile to high performance computing and also safety-critical applications.
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 readers with a comprehensive, state-of-the-art overview of approximate computing, enabling the design trade-off of accuracy for achieving better power/performance efficiencies, through the simplification of underlying computing resources. The authors describe in detail various efforts to generate approximate hardware systems, while still providing an overview of support techniques at other computing layers. The book is organized by techniques for various hardware components, from basic building blocks to general circuits and systems.
This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs.
This is the first book of a two-volume book set which introduces software defined chips. In this book, it introduces the conceptual evolution of software defined chips from the development of integrated circuits and computing architectures. Technical principles, characteristics and key issues of software defined chips are systematically analyzed. The hardware architecture design methods are described involving architecture design primitives, hardware design spaces and agile design methods. From the perspective of the compilation system, the complete process from high-level language to configuration contexts is introduced in detail. This book is suitable for scientists and researchers in the areas of electrical and electronic engineering and computer science. Postgraduate students, practitioners and professionals in related areas are also potentially interested in the topic of this book.
This book presents the proceedings of the 4th International Conference on Electronics and Signal Processing (ICESP 2023), which was held in Macau, China during January 13-15, 2023. The book consists of contributions from various authors from both academia and industry, focusing on a diverse aspect of signal processing and information communication systems. The published papers suggest cutting-edge solutions that contribute to the quest for the future applications and communicating systems. The book is a useful reference to research students, research fellows, and scientists and engineers in the corresponding fields.
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.
This book constitutes the refereed proceedings of the 26th European Conference on Genetic Programming, EuroGP 2023, held as part of EvoStar 2023, in Brno, Czech Republic, during April 12–14, 2023, and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EvoApplications. The 14 revised full papers and 8 short papers presented in this book were carefully reviewed and selected from 38 submissions. The wide range of topics in this volume reflects the current state of research in the field. The collection of papers cover topics including developing new variants of GP algorithms for both optimization and machine learning problems as well as exploring GP to address complex real-world problems.
This book focuses on computing devices and their design at various levels to combat variability. The authors provide a review of key concepts with particular emphasis on timing errors caused by various variability sources. They discuss methods to predict and prevent, detect and correct, and finally conditions under which such errors can be accepted; they also consider their implications on cost, performance and quality. Coverage includes a comparative evaluation of methods for deployment across various layers of the system from circuits, architecture, to application software. These can be combined in various ways to achieve specific goals related to observability and controllability of the variability effects, providing means to achieve cross layer or hybrid resilience.