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This book provides a single-source reference to the state-of-the-art of high-level programming models and compilation tool-chains for embedded system platforms. The authors address challenges faced by programmers developing software to implement parallel applications in embedded systems, where very often they are forced to rewrite sequential programs into parallel software, taking into account all the low level features and peculiarities of the underlying platforms. Readers will benefit from these authors’ approach, which takes into account both the application requirements and the platform specificities of various embedded systems from different industries. Parallel programming tool-chains are described that take as input parameters both the application and the platform model, then determine relevant transformations and mapping decisions on the concrete platform, minimizing user intervention and hiding the difficulties related to the correct and efficient use of memory hierarchy and low level code generation.
This Expert Guide gives you the techniques and technologies in embedded multicore to optimally design and implement your embedded system. Written by experts with a solutions focus, this encyclopedic reference gives you an indispensable aid to tackling the day-to-day problems when building and managing multicore embedded systems. Following an embedded system design path from start to finish, our team of experts takes you from architecture, through hardware implementation to software programming and debug. With this book you will learn: • What motivates multicore • The architectural options and tradeoffs; when to use what • How to deal with the unique hardware challenges that multicore presents • How to manage the software infrastructure in a multicore environment • How to write effective multicore programs • How to port legacy code into a multicore system and partition legacy software • How to optimize both the system and software • The particular challenges of debugging multicore hardware and software - Examples demonstrating timeless implementation details - Proven and practical techniques reflecting the authors' expertise built from years of experience and key advice on tackling critical issues
As in any complex architecture, debug and instrumentation resources are critical for multicore design. Debug instrumentation provides information for post-silicon debug analysis, software optimization, and performance monitoring. In this chapter, we introduce debug concepts useful for multicore; we deconstruct and discuss different debug instrumentation blocks and interfaces, including typical operations and system integration; and we discuss differences, considerations, and approaches more appropriate to multicore debug. This is followed by multicore debug examples, some of which are based on open standards and some on commercially-available blocks from processor IP providers.
This book covers a wide range of challenges, technologies and state-of-the-art for the design, development and realization of smart and complex embedded systems and their applications; i.e., software and hardware development, with the use of digital technologies, and quality assurance for critical applications. This book starts with automotive safety systems which is one of the major functional domains. It discusses the importance of software in automotive systems followed by an insight into Automotive Software Standards, ISO26262, and Autosar. The book further discusses the use of Processor in the loop test for an adaptive trajectory tracking control for quadrotor UAVs. It also illustrates the role of embedded systems in medical engineering. Various innovative applications involving the concept of image processing and Internet of Things are also presented in this book. The SoC Power Estimation is also investigated. Finally, a Review of the Hardware/Software Partitioning Algorithms with some future works have been presented. this book is intended for academicians, researchers, and industrialists.
The demands of increasingly complex embedded systems and associated performance computations have resulted in the development of heterogeneous computing architectures that often integrate several types of processors, analog and digital electronic components, and mechanical and optical components—all on a single chip. As a result, now the most prominent challenge for the design automation community is to efficiently plan for such heterogeneity and to fully exploit its capabilities. A compilation of work from internationally renowned authors, Model-Based Design for Embedded Systems elaborates on related practices and addresses the main facets of heterogeneous model-based design for embedded systems, including the current state of the art, important challenges, and the latest trends. Focusing on computational models as the core design artifact, this book presents the cutting-edge results that have helped establish model-based design and continue to expand its parameters. The book is organized into three sections: Real-Time and Performance Analysis in Heterogeneous Embedded Systems, Design Tools and Methodology for Multiprocessor System-on-Chip, and Design Tools and Methodology for Multidomain Embedded Systems. The respective contributors share their considerable expertise on the automation of design refinement and how to relate properties throughout this refinement while enabling analytic and synthetic qualities. They focus on multi-core methodological issues, real-time analysis, and modeling and validation, taking into account how optical, electronic, and mechanical components often interface. Model-based design is emerging as a solution to bridge the gap between the availability of computational capabilities and our inability to make full use of them yet. This approach enables teams to start the design process using a high-level model that is gradually refined through abstraction levels to ultimately yield a prototype. When executed well, model-based design encourages enhanced performance and quicker time to market for a product. Illustrating a broad and diverse spectrum of applications such as in the automotive aerospace, health care, consumer electronics, this volume provides designers with practical, readily adaptable modeling solutions for their own practice.
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
This book comprises select peer-reviewed papers from the International Conference on IoT, Intelligent Computing and Security, IICS 2021. The contents focus on the latest research in artificial intelligence, IoT, intelligent computing, and leading technological convergence security challenges. The book also discusses AI-driven automation of highly connected smart devices across the globe presenting the fast technological shift with the futuristic scenario, bursting perspective of IoT, computational intelligence, and security concerns. This book supports the transfer of vital knowledge to the next generation of researchers, students, and practitioners in academia and industry.
Information and Communication Technology for Sustainable Development shows how ICT, as an enabler for all spheres of development, can help innovate business processes and operations, and provide faster integration of new technologies into business systems. Focused on sustainability, the book addresses strategic approaches to cope with a range of climatic, environmental, cyber-security threats and other global risks, and aims to promote prosperity and economic growth. Furthermore, it explores how the adoption of new technologies, and collective action based upon a strategic behavioral theory of new leadership, can be applied when responding to specific set of conditions that allow for the proposed strategies to cope with risks. Information technology and strategic planning complement each other to attain the sustainable development goals (SDGs). Risk management frameworks, business continuity systems, and strategic planning methodologies such as mechanism design theory, strategic adaptive cognition (SAC), and risk mechanism theory (RMT) are the fundamental components needed to have a universal approach embedded into the national development plans agenda. As technology no longer follows an orderly, linear path, but improves exponentially, developing a strategic approach to ICT implementation help world leaders in the difficult but inspiring task of making a sustainable world and consequently find solutions to achieve the SDGs and the desired growth pattern that must be sustained, inclusive and equitable. Features: Discusses for the first time the potential of ICT as a transformative power in finding solutions to climatic and economic issues. Illustrates comprehensive strategic planning for leaders to implement in both public and private organizations. Integrates standards and frameworks in the context of sustainable development along with the UN Sustainable Development Goals. Describes in detail how mechanism design, risk management, business continuity systems, a comprehensive strategic planning using SAC (Strategic Adaptive Cognition) and risk mechanism theory can be used to address environmental risks and attain sustainable development goals (SDGs). Explains eHealth as an adaptation strategy to address future changes in climate and impacts, and the links between mitigation and adaptation to ICTs.
This book includes original, peer-reviewed articles from the 2nd International Conference on Cognitive & Intelligent Computing (ICCIC-2022), held at Vasavi College of Engineering Hyderabad, India. It covers the latest trends and developments in areas of cognitive computing, intelligent computing, machine learning, smart cities, IoT, artificial intelligence, cyber-physical systems, cybernetics, data science, neural network, and cognition. This book addresses the comprehensive nature of computational intelligence, cognitive computing, AI, ML, and DL to emphasize its character in modeling, identification, optimization, prediction, forecasting, and control of future intelligent systems. Submissions are original, unpublished, and present in-depth fundamental research contributions either from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications.