Static Resource Models For Code Generation Of Embedded Processors

This title covers all software-related aspects of SoC design, from embedded and application-domain specific operating systems to system architecture for future SoC. It will give embedded software designers invaluable insights into the constraints imposed by the use of embedded software in an SoC context.

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.

One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under various types of users with evolving relationships fraught with uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems. This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics. This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics.

Today more than 90% of all programmable processors are employed in embedded systems. The LISA processor design platform presented in this book addresses recent design challenges and results in highly satisfactory solutions, covering all major high-level phases of embedded processor design.

From Model-Driven Design to Resource Management for Distributed Embedded Systems presents 16 original contributions and 12 invited papers presented at the Working Conference on Distributed and Parallel Embedded Systems - DIPES 2006, sponsored by the International Federation for Information Processing - IFIP. Coverage includes model-driven design, testing and evolution of embedded systems, timing analysis and predictability, scheduling, allocation, communication and resource management in distributed real-time systems.

This book constitutes the refereed proceedings of the Second International Conference on Embedded Software, EMSOFT 2002, held in Grenoble, France in October 2002. The book presents 13 invited papers by leading researchers and 17 revised full papers selected during a competitive round of reviewing. The book spans the whole range of embedded software, including operating systems and middleware, programming languages and compilers, modeling and validation, software engineering and programming methodologies, scheduling and execution-time analysis, formal methods, and communication protocols and fault-tolerance