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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. Presents an overview of the approximate arithmetic building blocks that can be used for designing power/performance efficient computing units; Discusses effective memory approximation techniques to employ in conventional, i.e., DRAM and SRAM, as well as emerging, i.e., PCM and STT-RAM, memory technologies, for improving performance, power, and/or energy efficiency of the memory for error resilient applications; Includes an overview of hardware or software/hardware approximation techniques that operate across entire computing devices, including processors, graphical processors, and accelerators that can form a SoC with processors.

Computer algorithms. --- Embedded computer systems. --- Approximation theory. --- Systems engineering. --- Computer science. --- Electronics. --- Circuits and Systems. --- Processor Architectures. --- Electronics and Microelectronics, Instrumentation. --- Electrical engineering --- Physical sciences --- Informatics --- Science --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Design and construction --- Electronic circuits. --- Microprocessors. --- Microelectronics. --- Minicomputers --- Electron-tube circuits --- Electric circuits --- Electron tubes --- Electronics --- Microminiature electronic equipment --- Microminiaturization (Electronics) --- Microtechnology --- Semiconductors --- Miniature electronic equipment

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This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

Embedded computer systems. --- Electronic circuits. --- Cooperating objects (Computer systems). --- Embedded Systems. --- Electronic Circuits and Systems. --- Cyber-Physical Systems.

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Electrical engineering --- Computer architecture. Operating systems --- embedded systems --- multimedia --- architectuur (informatica) --- elektrische circuits

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This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

Embedded computer systems. --- Cooperating objects (Computer systems). --- Artificial intelligence. --- Embedded Systems. --- Cyber-Physical Systems. --- Artificial Intelligence. --- Sistemes incrustats (Informàtica) --- Objectes cooperants (Sistemes informàtics) --- Informàtica a la perifèria --- Aprenentatge automàtic

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The extreme complexity/energy requirements and context-aware processing nature of multimedia applications stimulate the need for adaptive low-power embedded multimedia systems with high-performance. Run-time adaptivity is required to react to the run-time varying scenarios (e.g., quality and performance constraints, available energy, input data).  This book presents techniques for energy reduction in adaptive embedded multimedia systems, based on dynamically reconfigurable processors.  The approach described will enable designers to meet performance/area constraints, while minimizing video quality degradation, under various, run-time scenarios.  Emphasis is placed on implementing power/energy reduction at various abstraction levels. To enable this, novel techniques for adaptive energy management at both processor architecture and application architecture levels are presented, such that both hardware and software adapt together, minimizing overall energy consumption under unpredictable, design-/compile-time scenarios.   Introduces general concepts and requirements of embedded multimedia systems based on advanced video codecs, dynamically reconfigurable processors, and low-power techniques in reconfigurable computing; Describes novel techniques and concepts for providing adaptivity and energy reduction jointly at processor and application architecture levels; Provides techniques for enabling run-time configurability for quality vs. energy consumption tradeoff at the application level

Electrical engineering --- Computer architecture. Operating systems --- embedded systems --- multimedia --- architectuur (informatica) --- elektrische circuits