Creativity in Computing and DataFlow Supercomputing, the latest release in the Advances in Computers series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore topics in greater depth and breadth than journal articles typically allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

The demand is exploding for complete, integrated systems that sense, process, manipulate, and control complex entities such as sound, images, text, motion, and environmental conditions. These systems, from hand-held devices to automotive sub-systems to aerospace vehicles, employ electronics to manage and adapt to a world that is, predominantly, neither digital nor electronic.

To respond to this design challenge, the industry has developed and standardized VHDL-AMS, a unified design language for modeling digital, analog, mixed-signal, and mixed-technology systems. VHDL-AMS extends VHDL to bring the successful HDL modeling methodology of digital electronic systems design to these new design disciplines.

Gregory Peterson and Darrell Teegarden join best-selling author Peter Ashenden in teaching designers how to use VHDL-AMS to model these complex systems. This comprehensive tutorial and reference provides detailed descriptions of both the syntax and semantics of the language and of successful modeling techniques. It assumes no previous knowledge of VHDL, but instead teaches VHDL and VHDL-AMS in an integrated fashion, just as it would be used by designers of these complex, integrated systems.
* Explores the design of an electric-powered, unmanned aerial vehicle system (UAV) in five separate case studies to illustrate mixed-signal, mixed-technology, power systems, communication systems, and full system modeling.
* Includes a CD-ROM with code for all the examples and case studies in the book, an educational model library, a quick reference guide for VHDL-AMS, a syntax reference from Appendix E in the book, links to VHDL-AMS resources and Mentor Graphics SystemVision software, which provides a simulation and modeling environment with a schematic entry tool, a VHDL-AMS simulator, and a waveform viewing facility.

A complete and authoritative discussion of systems engineering and neural networks In Systems Engineering Neural Networks, a team of distinguished researchers deliver a thorough exploration of the fundamental concepts underpinning the creation and improvement of neural networks with a systems engineering mindset. In the book, you'll find a general theoretical discussion of both systems engineering and neural networks accompanied by coverage of relevant and specific topics, from deep learning fundamentals to sport business applications. Readers will discover in-depth examples derived from many years of engineering experience, a comprehensive glossary with links to further reading, and supplementary online content. The authors have also included a variety of applications programmed in both Python 3 and Microsoft Excel. The book provides: A thorough introduction to neural networks, introduced as key element of complex systems Practical discussions of systems engineering and forecasting, complexity theory and optimization and how these techniques can be used to support applications outside of the traditional AI domains Comprehensive explorations of input and output, hidden layers, and bias in neural networks, as well as activation functions, cost functions, and back-propagation Guidelines for software development incorporating neural networks with a systems engineering methodology Perfect for students and professionals eager to incorporate machine learning techniques into their products and processes, Systems Engineering Neural Networks will also earn a place in the libraries of managers and researchers working in areas involving neural networks.

Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks. This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning.

Advances in Delay-Tolerant Networks: Architecture and Enhanced Performance, Second Edition provides an important overview of delay-tolerant networks (DTNs) for researchers in electronics, computer engineering, telecommunications and networking for those in academia and R&D in industrial sectors. Part I reviews the technology involved and the prospects for improving performance, including different types of DTN and their applications, such as satellite and deep-space communications and vehicular communications. Part II focuses on how the technology can be further improved, addressing topics, such as data bundling, opportunistic routing, reliable data streaming, and the potential for rapid selection and dissemination of urgent messages. Opportunistic, delay-tolerant networks address the problem of intermittent connectivity in a network where there are long delays between sending and receiving messages, or there are periods of disconnection.

Shape grammar and space syntax have been separately developed but rarely combined in any significant way. The first of these is typically used to investigate or generate the formal or geometric properties of architecture, while the second is used to analyze the spatial, topological, or social properties of architecture. Despite the reciprocal relationship between form and space in architecture-it is difficult to conceptualize a completed building without a sense of both of these properties-the two major computational theories have been largely developed and applied in isolation from each another. Grammatical and Syntactical Approaches in Architecture: Emerging Research and Opportunities is a critical scholarly resource that explores the relationship between shape grammar and space syntax for urban planning and architecture and enables the creative discovery of both the formal and spatial features of an architectural style or type. This book, furthermore, presents a new method to selectively capture aspects of both the grammar and syntax of architecture. Featuring a range of topics such as mathematical analysis, spatial configuration, and domestic architecture, this book is essential for architects, policymakers, urban planners, researchers, academicians, and students.

If you look around you will find that all computer systems, from your portable devices to the strongest supercomputers, are heterogeneous in nature. The most obvious heterogeneity is the existence of computing nodes of different capabilities (e.g. multicore, GPUs, FPGAs, ...). But there are also other heterogeneity factors that exist in computing systems, like the memory system components, interconnection, etc. The main reason for these different types of heterogeneity is to have good performance with power efficiency. Heterogeneous computing results in both challenges and opportunities. This book discusses both. It shows that we need to deal with these challenges at all levels of the computing stack: from algorithms all the way to process technology. We discuss the topic of heterogeneous computing from different angles: hardware challenges, current hardware state-of-the-art, software issues, how to make the best use of the current heterogeneous systems, and what lies ahead. The aim of this book is to introduce the big picture of heterogeneous computing. Whether you are a hardware designer or a software developer, you need to know how the pieces of the puzzle fit together. The main goal is to bring researchers and engineers to the forefront of the research frontier in the new era that started a few years ago and is expected to continue for decades. We believe that academics, researchers, practitioners, and students will benefit from this book and will be prepared to tackle the big wave of heterogeneous computing that is here to stay.

As technology continues to advance in today's global market, practitioners are targeting systems with significant levels of applicability and variance. Instrumentation is a multidisciplinary subject that provides a wide range of usage in several professional fields, specifically engineering. Instrumentation plays a key role in numerous daily processes and has seen substantial advancement in recent years. It is of utmost importance for engineering professionals to understand the modern developments of instruments and how they affect everyday life. Advancements in Instrumentation and Control in Applied System Applications is a collection of innovative research on the methods and implementations of instrumentation in real-world practices including communication, transportation, and biomedical systems. While highlighting topics including smart sensor design, medical image processing, and atrial fibrillation, this book is ideally designed for researchers, software engineers, technologists, developers, scientists, designers, IT professionals, academicians, and post-graduate students seeking current research on recent developments within instrumentation systems and their applicability in daily life.

Though traditionally information systems have been centralized, these systems are now distributed over the web. This requires a re-investigation into the way information systems are modeled and designed. Because of this new function, critical problems, including security, never-fail systems, and quality of service have begun to emerge. Novel Approaches to Information Systems Design is an essential publication that explores the most recent, cutting-edge research in information systems and exposes the reader to emerging but relatively mature models and techniques in the area. Highlighting a wide range of topics such as big data, business intelligence, and energy efficiency, this publication is ideally designed for managers, administrators, system developers, information system engineers, researchers, academicians, and graduate-level students seeking coverage on critical components of information systems.

The Physics of Computing gives a foundational view of the physical principles underlying computers. Performance, power, thermal behavior, and reliability are all harder and harder to achieve as transistors shrink to nanometer scales. This book describes the physics of computing at all levels of abstraction from single gates to complete computer systems. It can be used as a course for juniors or seniors in computer engineering and electrical engineering, and can also be used to teach students in other scientific disciplines important concepts in computing. For electrical engineering, the book provides the fundamentals of computing that link core concepts to computing. For computer science, it provides foundations of key challenges such as power consumption, performance, and thermal. The book can also be used as a technical reference by professionals.

Parallelism is the key to achieving high performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under many different settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era. The first part of this thesis introduces tools and techniques for deterministic parallel programming, including means for encapsulating nondeterminism via powerful commutative building blocks, as well as a novel framework for executing sequential iterative loops in parallel, which lead to deterministic parallel algorithms that are efficient both in theory and in practice. The second part of this thesis introduces Ligra, the first high-level shared memory framework for parallel graph traversal algorithms. The framework allows programmers to express graph traversal algorithms using very short and concise code, delivers performance competitive with that of highly-optimized code, and is up to orders of magnitude faster than existing systems designed for distributed memory. This part of the thesis also introduces Ligra , which extends Ligra with graph compression techniques to reduce space usage and improve parallel performance at the same time, and is also the first graph processing system to support in-memory graph compression. The third and fourth parts of this thesis bridge the gap between theory and practice in parallel algorithm design by introducing the first algorithms for a variety of important problems on graphs and strings that are efficient both in theory and in practice. For example, the thesis develops the first linear-work and polylogarithmic-depth algorithms for suffix tree construction and graph connectivity that are also practical, as well as a work-efficient, polylogarithmic-depth, and cache-efficient shared-memory algorithm for triangle computations that achieves a 2-5x speedup over the best existing algorithms on 40 cores. This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.

Model Driven Architecture (MDA) is a new approach to software development that helps companies manage large, complex software projects and save development costs while allowing new technologies that come along to be readily incorporated. Although it is based on many long-standing industry precepts and best practices, such as UML, it is enough of a departure from traditional IT approaches to require some "proof of the pudding." Real-Life MDA is composed of six case studies of real companies using MDA that will furnish that proof. The authors' approach MDA projects by describing all aspects of the project from the viewpoint of the end-usersfrom the reason for choosing an MDA approach to the results and benefits. The case studies are preceded by an introductory chapter and are followed by a wrap-up chapter summarizing lessons learned.
* Written for executives, analysts, architects, and engineers positioned to influence business-oriented software development at the highest levels.
* Filled with concrete examples and analyses of how MDA is relevant for organizations of various sizes.
* Considers a range of uses for MDA from business process analysis to full-scale software modeling and development.
* Presents results for each case study in terms of tangible, measured benefits, including automatically generated code, defect reduction, improved visibility, and ROI."

Intelligent systems and related designs have become important instruments leading to profound innovations in automated control and interaction with computers and machines. Such systems depend upon established methods and tools for solving complex learning and decision-making problems under uncertain and continuously varying conditions. Intelligent Applications for Heterogeneous System Modeling and Design examines the latest developments in intelligent system engineering being used across industries with an emphasis on transportation, aviation, and medicine. Focusing on the latest trends in artificial intelligence, systems design and testing, and related topic areas, this publication is designed for use by engineers, IT specialists, academicians, and graduate-level students.

Networks-on-Chip: From Implementations to Programming Paradigms provides a thorough and bottom-up exploration of the whole NoC design space in a coherent and uniform fashion, from low-level router, buffer and topology implementations, to routing and flow control schemes, to co-optimizations of NoC and high-level programming paradigms.

This lecture is intended for an advanced course on computer architecture, suitable for graduate students or senior undergrads who want to specialize in the area of computer architecture and Networks-on-Chip. It is also intended for practitioners in the industry in the area of microprocessor design, especially the many-core processor design with a network-on-chip. The graduates can learn many practical and theoretical lessons from this course, and also can be motivated to delve further into the ideas and designs proposed in this book. The industrial engineers can refer this book to make practicing tradeoffs as well. The graduates and engineers focus on off-chip network design can also refer this book for deadlock-free routing algorithm designs.
Provides thorough and insightful exploration of NoC design space. Description from low-level logic implementations to co-optimizations of high-level program paradigms and NoCs.The coherent and uniform description fashion offers the readers a clear, quick and efficient exploration of NoC design spaceCovers many novel and exciting research ideas, which encourage researchers to further delve into these topics.Presents both engineering and theoretical contributions. The detailed description of the router, buffer and topology implementations, comparisons and analysis are of high engineering value.

Architecting High Performing, Scalable and Available Enterprise Web Applications provides in-depth insights into techniques for achieving desired scalability, availability and performance quality goals for enterprise web applications. The book provides an integrated 360-degree view of achieving and maintaining these attributes through practical, proven patterns, novel models, best practices, performance strategies, and continuous improvement methodologies and case studies. The author shares his years of experience in application security, enterprise application testing, caching techniques, production operations and maintenance, and efficient project management techniques.

"High-Performance Embedded Computing, Second Edition," combines leading-edge research with practical guidance in a variety of embedded computing topics, including real-time systems, computer architecture, and low-power design. Author Marilyn Wolf presents a comprehensive survey of the state of the art, and guides you to achieve high levels of performance from the embedded systems that bring these technologies together.

The book covers CPU design, operating systems, multiprocessor programs and architectures, and much more. Embedded computing is a key component of cyber-physical systems, which combine physical devices with computational resources for control and communication. This revised edition adds new content and examples of cyber-physical systems throughout the book, including design methodologies, scheduling, and wide-area CPS to illustrate the possibilities of these new systems.
Revised and updated with coverage of recently developed consumer electronics architectures and models of computingIncludes new VLIW processors such as the TI Da Vinci, and CPU simulation Learn model-based verification and middleware for embedded systems Supplemental material includes lecture slides, labs, and additional resources"

Service orchestration techniques combine the benefits of Service Oriented Architecture (SOA) and Business Process Management (BPM) to compose and coordinate distributed software services. On the other hand, Software-as-a-Service (SaaS) is gaining popularity as a software delivery model through cloud platforms due to the many benefits to software vendors, as well as their customers. Multi-tenancy, which refers to the sharing of a single application instance across multiple customers or user groups (called tenants), is an essential characteristic of the SaaS model. Written in an easy to follow style with discussions supported by real-world examples, Service Orchestration as Organization introduces a novel approach with associated language, framework, and tool support to show how service orchestration techniques can be used to engineer and deploy SaaS applications.