Alexander Biedermann presents a generic hardware-based virtualization approach, which may transform an array of any off-the-shelf embedded processors into a multi-processor system with high execution dynamism. Based on this approach, he highlights concepts for the design of energy aware systems, self-healing systems as well as parallelized systems. For the latter, the novel so-called Agile Processing scheme is introduced by the author, which enables a seamless transition between sequential and parallel execution schemes. The design of such virtualizable systems is further aided by introduction of a dedicated design framework, which integrates into existing, commercial workflows. As a result, this book provides comprehensive design flows for the design of embedded multi-processor systems-on-chip.

Despite its importance, the role of HdS is most often underestimated and the topic is not well represented in literature and education. To address this, Hardware-dependent Software brings together experts from different HdS areas. By providing a comprehensive overview of general HdS principles, tools, and applications, this book provides adequate insight into the current technology and upcoming developments in the domain of HdS. The reader will find an interesting text book with self-contained introductions to the principles of Real-Time Operating Systems (RTOS), the emerging BIOS successor UEFI, and the Hardware Abstraction Layer (HAL). Other chapters cover industrial applications, verification, and tool environments. Tool introductions cover the application of tools in the ASIP software tool chain (i.e. Tensilica) and the generation of drivers and OS components from C-based languages. Applications focus on telecommunication and automotive systems.

This title serves as an introduction ans reference for the field, with the papers that have shaped the hardware/software co-design since its inception in the early 90s.

Details a real-world product that applies a cutting-edge multi-core architecture Increasingly demanding modern applications—such as those used in telecommunications networking and real-time processing of audio, video, and multimedia streams—require multiple processors to achieve computational performance at the rate of a few giga-operations per second. This necessity for speed and manageable power consumption makes it likely that the next generation of embedded processing systems will include hundreds of cores, while being increasingly programmable, blending processors and configurable hardware in a power-efficient manner. Multi-Core Embedded Systems presents a variety of perspectives that elucidate the technical challenges associated with such increased integration of homogeneous (processors) and heterogeneous multiple cores. It offers an analysis that industry engineers and professionals will need to understand the physical details of both software and hardware in embedded architectures, as well as their limitations and potential for future growth. Discusses the available programming models spread across different abstraction levels The book begins with an overview of the evolution of multiprocessor architectures for embedded applications and discusses techniques for autonomous power management of system-level parameters. It addresses the use of existing open-source (and free) tools originating from several application domains—such as traffic modeling, graph theory, parallel computing and network simulation. In addition, the authors cover other important topics associated with multi-core embedded systems, such as: Architectures and interconnects Embedded design methodologies Mapping of applications

This book provides readers with an overview of the architectures, programming frameworks, and hardware accelerators for typical cloud computing applications in data centers. The authors present the most recent and promising solutions, using hardware accelerators to provide high throughput, reduced latency and higher energy efficiency compared to current servers based on commodity processors. Readers will benefit from state-of-the-art information regarding application requirements in contemporary data centers, computational complexity of typical tasks in cloud computing, and a programming framework for the efficient utilization of the hardware accelerators.

This book collects selected papers from the 7th Conference on Signal and Information Processing, Networking and Computers held in Rizhao, China, on September 21-23, 2020. The 7th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) was held in Rizhao, China, on September 21-23, 2020.

This book introduces a modern approach to embedded system design, presenting software design and hardware design in a unified manner. It covers trends and challenges, introduces the design and use of single-purpose processors ("hardware") and general-purpose processors ("software"), describes memories and buses, illustrates hardware/software tradeoffs using a digital camera example, and discusses advanced computation models, controls systems, chip technologies, and modern design tools. For courses found in EE, CS and other engineering departments.

This book constitutes the refereed proceedings of the 5th International Workshop on Systems, Architectures, Modeling, and Simulation, SAMOS 2005, held in Samos, Greece in July 2005. The 49 revised full papers presented were thoroughly reviewed and selected from 114 submissions. The papers are organized in topical sections on reconfigurable system design and implementations, processor architectures, design and simulation, architectures and implementations, system level design, and modeling and simulation.

Heterogeneous Computing with OpenCL, Second Edition teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. It is the first textbook that presents OpenCL programming appropriate for the classroom and is intended to support a parallel programming course. Students will come away from this text with hands-on experience and significant knowledge of the syntax and use of OpenCL to address a range of fundamental parallel algorithms. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, Heterogeneous Computing with OpenCL explores memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. It includes detailed examples throughout, plus additional online exercises and other supporting materials that can be downloaded at http://www.heterogeneouscompute.org/?page_id=7 This book will appeal to software engineers, programmers, hardware engineers, and students/advanced students. Explains principles and strategies to learn parallel programming with OpenCL, from understanding the four abstraction models to thoroughly testing and debugging complete applications. Covers image processing, web plugins, particle simulations, video editing, performance optimization, and more. Shows how OpenCL maps to an example target architecture and explains some of the tradeoffs associated with mapping to various architectures Addresses a range of fundamental programming techniques, with multiple examples and case studies that demonstrate OpenCL extensions for a variety of hardware platforms

Advances in GPU Research and Practice focuses on research and practices in GPU based systems. The topics treated cover a range of issues, ranging from hardware and architectural issues, to high level issues, such as application systems, parallel programming, middleware, and power and energy issues. Divided into six parts, this edited volume provides the latest research on GPU computing. Part I: Architectural Solutions focuses on the architectural topics that improve on performance of GPUs, Part II: System Software discusses OS, compilers, libraries, programming environment, languages, and paradigms that are proposed and analyzed to help and support GPU programmers. Part III: Power and Reliability Issues covers different aspects of energy, power, and reliability concerns in GPUs. Part IV: Performance Analysis illustrates mathematical and analytical techniques to predict different performance metrics in GPUs. Part V: Algorithms presents how to design efficient algorithms and analyze their complexity for GPUs. Part VI: Applications and Related Topics provides use cases and examples of how GPUs are used across many sectors. - Discusses how to maximize power and obtain peak reliability when designing, building, and using GPUs - Covers system software (OS, compilers), programming environments, languages, and paradigms proposed to help and support GPU programmers - Explains how to use mathematical and analytical techniques to predict different performance metrics in GPUs - Illustrates the design of efficient GPU algorithms in areas such as bioinformatics, complex systems, social networks, and cryptography - Provides applications and use case scenarios in several different verticals, including medicine, social sciences, image processing, and telecommunications