A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues.

A unique feature of this textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This third edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems and the Internet of things, the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues.

This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems. The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.

This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems. The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.

For real-time systems, the worst-case execution time (WCET) is the key objective to be considered. Traditionally, code for real-time systems is generated without taking this objective into account and the WCET is computed only after code generation. Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems presents the first comprehensive approach integrating WCET considerations into the code generation process. Based on the proposed reconciliation between a compiler and a timing analyzer, a wide range of novel optimization techniques is provided. Among others, the techniques cover source code and assembly level optimizations, exploit machine learning techniques and address the design of modern systems that have to meet multiple objectives. Using these optimizations, the WCET of real-time applications can be reduced by about 30% to 45% on the average. This opens opportunities for decreasing clock speeds, costs and energy consumption of embedded processors. The proposed techniques can be used for all types real-time systems, including automotive and avionics IT systems.

Modern electronics is driven by the explosive growth of digital communications and multi-media technology. A basic challenge is to design first-time-right complex digital systems, that meet stringent constraints on performance and power dissipation. In order to combine this growing system complexity with an increasingly short time-to-market, new system design technologies are emerging based on the paradigm of embedded programmable processors. This concept introduces modularity, flexibility and re-use in the electronic system design process. However, its success will critically depend on the availability of efficient and reliable CAD tools to design, programme and verify the functionality of embedded processors. Recently, new research efforts emerged on the edge between software compilation and hardware synthesis, to develop high-quality code generation tools for embedded processors. Code Generation for Embedded Systems provides a survey of these new developments. Although not limited to these targets, the main emphasis is on code generation for modern DSP processors. Important themes covered by the book include: the scope of general purpose versus application-specific processors, machine code quality for embedded applications, retargetability of the code generation process, machine description formalisms, and code generation methodologies. Code Generation for Embedded Systems is the essential introduction to this fast developing field of research for students, researchers, and practitioners alike.

Many of the modern applications of microelectronics require hugeamounts of computations. Despite all recent improvements in fabrication technologies, some of these computations have to be performed in hardware in order to meet deadlines. However, controlling computations by software is frequently pre ferred due to the larger flexibility. Hence, in general, modern applications re quire a mix of software-based and hardware-based computations. Applications using this mix can be designed with the help of hardware/software co-design systems. Many such co-design systems have been described so far (references can be found in this book), but many of these are based on heuristics. In this book, Niemann describes a co-design system which is based on sound modeling techniques. This system has the following salient features: * Precise cost and performance figures Design decisions for implementing a certain function in hardware or software are based on 'cost and performance figures for the different design alterna tives. Hence, good designs can only be expected if these figures are accurate. In order to achieve excellent accuracy, Niemann takes a new approach: the cost of software implementations is derived from the data available about the target processors and from knowledge about the code size. the performance of software implement at ions is computed by compiling the given function and then using static analysis for computing worst case execution times. the cost of hardware implementation is estimated by running higher-Ievel synthesis tools. the performance of hardware implementations is again computed by us ing static analysis.

It is well known that embedded systems have to be implemented efficiently. This requires that processors optimized for certain application domains are used in embedded systems. Such an optimization requires a careful exploration of the design space, including a detailed study of cost/performance tradeoffs. In order to avoid time-consuming assembly language programming during design space exploration, compilers are needed. In order to analyze the effect of various software or hardware configurations on the performance, retargetable compilers are needed that can generate code for numerous different potential hardware configurations. This book provides a comprehensive and up-to-date overview of the fast developing area of retargetable compilers for embedded systems. It describes a large set important tools as well as applications of retargetable compilers at different levels in the design flow. Retargetable Compiler Technology for Embedded Systems is mostly self-contained and requires only fundamental knowledge in software and compiler design. It is intended to be a key reference for researchers and designers working on software, compilers, and processor optimization for embedded systems.

This book proposes novel memory hierarchies and software optimization techniques for the optimal utilization of memory hierarchies. It presents a wide range of optimizations, progressively increasing in the complexity of analysis and of memory hierarchies. The final chapter covers optimization techniques for applications consisting of multiple processes found in most modern embedded devices.

The memory system is increasingly turning into a bottleneck in the design of embedded systems. The speed improvements of memory systems are lower than the speed improvements of processors, eventually leading to embedded systems whose performance is limited by the memory. This problem is known as the "memory wall" problem. Furthermore, memory systems may consume the largest share of the system s energy budget and may be the source of unpredictable timing behaviour. Hence, the design of the memory system deserves an increasing amount of attention.

Fast, Efficient and Predictable Memory Accesses presents techniques for designing fast, energy-efficient and timing predictable memory systems. By using a careful combination of compiler optimizations and architectural improvements, we can achieve more than what would be feasible at one of the levels in isolation. The described optimization algorithms achieve the goals of high performance and low energy consumption. In addition to these benefits, the use of scratchpad memories significantly improves the timing predictability of the entire system, leading to tighter worst case execution time bounds (WCET). The WCET is a relevant design parameter for all timing critical systems. In addition, the book covers algorithms to exploit the power down modes of main memories in SDRAM technology, as well as the execute-in-place feature of Flash memories. The final chapter considers the impact of the register file, which is also part of the memory hierarchy."

For real-time systems, the worst-case execution time (WCET) is the key objective to be considered. Traditionally, code for real-time systems is generated without taking this objective into account and the WCET is computed only after code generation. Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems presents the first comprehensive approach integrating WCET considerations into the code generation process. Based on the proposed reconciliation between a compiler and a timing analyzer, a wide range of novel optimization techniques is provided. Among others, the techniques cover source code and assembly level optimizations, exploit machine learning techniques and address the design of modern systems that have to meet multiple objectives.

Using these optimizations, the WCET of real-time applications can be reduced by about 30% to 45% on the average. This opens opportunities for decreasing clock speeds, costs and energy consumption of embedded processors. The proposed techniques can be used for all types real-time systems, including automotive and avionics IT systems.

The design of embedded systems warrants a new perspective because of the following two reasons: Firstly, slow and energy inefficient memory hierarchies have already become the bottleneck of the embedded systems. It is documented in the literature as the memory wall problem. Secondly, the software running on the contemporary embedded devices is becoming increasingly complex. It is also well understood that no silver bullet exists to solve the memory wall problem. Therefore, this book explores a collaborative approach by proposing novel memory hierarchies and software optimization techniques for the optimal utilization of these memory hierarchies. Linking memory architecture design with memory-architecture aware compilation results in fast, energy-efficient and timing predictable memory accesses.

Fast, Efficient and Predictable Memory Accesses presents techniques for designing fast, energy-efficient and timing predictable memory systems. By using a careful combination of compiler optimizations and architectural improvements, we can achieve more than what would be feasible at one of the levels in isolation. The described optimization algorithms achieve the goals of high performance and low energy consumption. In addition to these benefits, the use of scratchpad memories significantly improves the timing predictability of the entire system, leading to tighter worst case execution time bounds (WCET). The WCET is a relevant design parameter for all timing critical systems. In addition, the book covers algorithms to exploit the power down modes of main memories in SDRAM technology, as well as the execute-in-place feature of Flash memories. The final chapter considers the impact of the register file, which is also part of the memory hierarchy.

It is well known that embedded systems have to be implemented efficiently. This requires that processors optimized for certain application domains are used in embedded systems. Such an optimization requires a careful exploration of the design space, including a detailed study of cost/performance tradeoffs. In order to avoid time-consuming assembly language programming during design space exploration, compilers are needed. In order to analyze the effect of various software or hardware configurations on the performance, retargetable compilers are needed that can generate code for numerous different potential hardware configurations. This book provides a comprehensive and up-to-date overview of the fast developing area of retargetable compilers for embedded systems. It describes a large set important tools as well as applications of retargetable compilers at different levels in the design flow. Retargetable Compiler Technology for Embedded Systems is mostly self-contained and requires only fundamental knowledge in software and compiler design. It is intended to be a key reference for researchers and designers working on software, compilers, and processor optimization for embedded systems.

The design process of embedded systems has changed substantially in recent years. One of the main reasons for this change is the pressure to shorten time-to-market when designing digital systems. To shorten the product cycles, programmable processes are used to implement more and more functionality of the embedded system. Therefore, nowadays, embedded systems are very often implemented by heterogeneous systems consisting of ASICs, processors, memories and peripherals. As a consequence, the research topic of hardware/software co-design, dealing with the problems of designing these heterogeneous systems, has gained great importance. Hardware/Software Co-design for Data Flow Dominated Embedded Systems introduces the different tasks of hardware/software co-design including system specification, hardware/software partitioning, co-synthesis and co-simulation. The book summarizes and classifies state-of-the-art co-design tools and methods for these tasks. In addition, the co-design tool COOL is presented which solves the co-design tasks for the class of data-flow dominated embedded systems. In Hardware/Software Co-design for Data Flow Dominated Embedded Systems the primary emphasis has been put on the hardware/software partitioning and the co-synthesis phase and their coupling. In contrast to many other publications in this area, a mathematical formulation of the hardware/software partitioning problem is given. This problem formulation supports target architectures consisting of multiple processors and multiple ASICs. Several novel approaches are presented and compared for solving the partitioning problem, including an MILP approach, a heuristic solution and an approach based on geneticalgorithms. The co-synthesis phase is based on the idea of controlling the system by means of a static run-time scheduler implemented in hardware. New algorithms are introduced which generate a complete set of hardware and software specifications required to implement heterogeneous systems. All of these techniques are described in detail and exemplified. Hardware/Software Co-design for Data Flow Dominated Embedded Systems is intended to serve students and researchers working on hardware/software co-design. At the same time the variety of presented techniques automating the design tasks of hardware/software systems will be of interest to industrial engineers and designers of digital systems. From the foreword by Peter Marwedel: Niemann's method should be known by all persons working in the field. Hence, I recommend this book for everyone who is interested in hardware/software co-design.

Modern electronics is driven by the explosive growth of digital communications and multi-media technology. A basic challenge is to design first-time-right complex digital systems, that meet stringent constraints on performance and power dissipation. In order to combine this growing system complexity with an increasingly short time-to-market, new system design technologies are emerging based on the paradigm of embedded programmable processors. This concept introduces modularity, flexibility and re-use in the electronic system design process. However, its success will critically depend on the availability of efficient and reliable CAD tools to design, programme and verify the functionality of embedded processors. Recently, new research efforts emerged on the edge between software compilation and hardware synthesis, to develop high-quality code generation tools for embedded processors. Code Generation for Embedded Systems provides a survey of these new developments. Although not limited to these targets, the main emphasis is on code generation for modern DSP processors. Important themes covered by the book include: the scope of general purpose versus application-specific processors, machine code quality for embedded applications, retargetability of the code generation process, machine description formalisms, and code generation methodologies. Code Generation for Embedded Systems is the essential introduction to this fast developing field of research for students, researchers, and practitioners alike.

Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering. Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to the different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Several machine learning methods are inspected with respect to their resource requirements and how to enhance their scalability on diverse computing architectures ranging from embedded systems to large computing clusters.

A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues.

This book focuses on source-to-source code transformations that remove addressing-related overhead present in most multimedia or signal processing application programs. This approach is complementary to existing compiler technology. What is particularly attractive about the transformation flow pre sented here is that its behavior is nearly independent of the target processor platform and the underlying compiler. Hence, the different source code trans formations developed here lead to impressive performance improvements on most existing processor architecture styles, ranging from RISCs like ARM7 or MIPS over Superscalars like Intel-Pentium, PowerPC, DEC-Alpha, Sun and HP, to VLIW DSPs like TI C6x and Philips TriMedia. The source code did not have to be modified between processors to obtain these results. Apart from the performance improvements, the estimated energy is also significantly reduced for a given application run. These results were not obtained for academic codes but for realistic and rep resentative applications, all selected from the multimedia domain. That shows the industrial relevance and importance of this research. At the same time, the scientific novelty and quality of the contributions have lead to several excellent papers that have been published in internationally renowned conferences like e. g. DATE. This book is hence of interest for academic researchers, both because of the overall description of the methodology and related work context and for the detailed descriptions of the compilation techniques and algorithms."