Most emerging applications in imaging and machine learning must perform immense amounts of computation while holding to strict limits on energy and power. To meet these goals, architects are building increasingly specialized compute engines tailored for these specific tasks. The resulting computer systems are heterogeneous, containing multiple processing cores with wildly different execution models. Unfortunately, the cost of producing this specialized hardware-and the software to control it-is astronomical. Moreover, the task of porting algorithms to these heterogeneous machines typically requires that the algorithm be partitioned across the machine and rewritten for each specific architecture, which is time consuming and prone to error. Over the last several years, the authors have approached this problem using domain-specific languages (DSLs): high-level programming languages customized for specific domains, such as database manipulation, machine learning, or image processing. By giving up generality, these languages are able to provide high-level abstractions to the developer while producing high-performance output. The purpose of this book is to spur the adoption and the creation of domain-specific languages, especially for the task of creating hardware designs. In the first chapter, a short historical journey explains the forces driving computer architecture today. Chapter 2 describes the various methods for producing designs for accelerators, outlining the push for more abstraction and the tools that enable designers to work at a higher conceptual level. From there, Chapter 3 provides a brief introduction to image processing algorithms and hardware design patterns for implementing them. Chapters 4 and 5 describe and compare Darkroom and Halide, two domain-specific languages created for image processing that produce high-performance designs for both FPGAs and CPUs from the same source code, enabling rapid design cycles and quick porting of algorithms. The final section describes how the DSL approach also simplifies the problem of interfacing between application code and the accelerator by generating the driver stack in addition to the accelerator configuration. This book should serve as a useful introduction to domain-specialized computing for computer architecture students and as a primer on domain-specific languages and image processing hardware for those with more experience in the field.

This book provides a unified overview of network-on-chip router micro-architecture, the corresponding design opportunities and challenges, and existing solutions to overcome these challenges. The discussion focuses on the heart of a NoC, the NoC router, and how it interacts with the rest of the system. Coverage includes both basic and advanced design techniques that cover the entire router design space including router organization, flow control, pipelined operation, buffering architectures, as well as allocators' structure and algorithms. Router micro-architectural options are presented in a step-by-step manner beginning from the basic design principles. Even highly sophisticated design alternatives are categorized and broken down to simpler pieces that can be understood easily and analyzed. This book is an invaluable reference for system, architecture, circuit, and EDA researchers and developers, who are interested in understanding the overall picture of NoC routers' architecture, the associated design challenges, and the available solutions.

An understanding of modern computer logic-incorporating core knowledge of number systems, number conversions, Boolean algebra, memories, and logic circuits-is fundamental to further study of computer architectures, system software, and computer networks. Computer Logic: Design Principles and Applications introduces and describes the relevant concepts, principles and applications of modern computer logic design. The book is self-contained, with an introductory chapter that concisely covers the history of computing devices, as well as number systems, number conversions, signed and unsigned integers, external code, and digital and digitizing concepts. Dedicated chapters on Boolean algebra, transistor circuits, combinatorial logic circuits, and sequential logic circuits round off the work. The emphasis is on design and applications. Topics and features: * Explains Boolean Algebra and logic design essentials in clear fashion * Includes modern topics, such as Unicode, Exclusive Or Theorems, unipolar transistors, copper technology, flash memory, Hardware Descriptive Language, and logic simulation software tools * Thorough coverage of combinatorial logic and provides numerous design examples, such as gates, decoders and encoders, comparators, carry-save and carry-propagated adders, multiplication trees, and programmable logic arrays * Provides chapter-by-chapter summary points, supplementary examples, and exercises * Sequential logic presented, with numerous design examples, such as flip-flops, counters, shift registers, sequencers, and excitation tables With its well-focused approach and clarity of presentation, this new text/reference is an excellent resource for advanced students and practitioners in computer science, computer engineering, and electrical engineering. Anyone seeking to develop a solid grounding in computer logic, circuit design, and logic design will find the book an essential and practical learning tool.

Network infrastructures are growing rapidly to meet the needs of business, but the required repolicing and reconfiguration provide challenges that need to be addressed. The software-defined network (SDN) is the future generation of Internet technology that can help meet these challenges of network management. This book includes quantitative research, case studies, conceptual papers, model papers, review papers, and theoretical backing on SDN. This book investigates areas where SDN can help other emerging technologies deliver more efficient services, such as IoT, industrial IoT, NFV, big data, blockchain, cloud computing, and edge computing. The book demonstrates the many benefits of SDNs, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. The book demonstrates the many benefits of SDN, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. Chapters in the volume address: Design considerations for security issues and detection methods State-of-the-art approaches for mitigating DDos attacks using SDN Big data using Apache Hadoop for processing and analyzing large amounts of data Different tools used for attack simulation Network policies and policy management approaches that are widely used in the context of SDN Dynamic flow tables, or static flow table management A new four-tiered architecture that includes cloud, SDN-controller, and fog computing Architecture for keeping computing resources available near the industrial IoT network through edge computing The impact of SDN as an innovative approach for smart city development More. The book will be a valuable resource for SDN researchers as well as academicians, research scholars, and students in the related areas.

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

This book equips readers with tools for computer architecture of high performance, low power, and high reliability memory hierarchy in computer systems based on emerging memory technologies, such as STTRAM, PCM, FBDRAM, etc. The techniques described offer advantages of high density, near-zero static power, and immunity to soft errors, which have the potential of overcoming the "memory wall." The authors discuss memory design from various perspectives: emerging memory technologies are employed in the memory hierarchy with novel architecture modification; hybrid memory structure is introduced to leverage advantages from multiple memory technologies; an analytical model named "Moguls" is introduced to explore quantitatively the optimization design of a memory hierarchy; finally, the vulnerability of the CMPs to radiation-based soft errors is improved by replacing different levels of on-chip memory with STT-RAMs.

In the 5G era, edge computing and new ecosystems of mobile microservices enable new business models, strategies, and competitive advantage. Focusing on microservices, this book introduces the essential concepts, technologies, and trade-offs in the edge computing architectural stack, providing for widespread adoption and dissemination. The book elucidates the concepts, architectures, well-defined building blocks, and prototypes for mobile microservice platforms and pervasive application development, as well as the implementation and configuration of service middleware and AI-based microservices. A goal-oriented service composition model is then proposed by the author, allowing for an economic assessment of connected, smart mobile services. Based on this model, costs can be minimized through statistical workload aggregation effects or backhaul data transport reduction, and customer experience and safety can be enhanced through reduced response times. This title will be a useful guide for students and IT professionals to get started with microservices and when studying the use of microservices in pervasive applications. It will also appeal to researchers and students studying software architecture and service-oriented computing, and especially those interested in edge computing, pervasive computing, the Internet of Things, and mobile microservices.

"Collaboration with Cloud Computing "discusses the risks associated with implementing these technologies across the enterprise and provides you with expert guidance on how to manage risk through policy changes and technical solutions.

Drawing upon years of practical experience and using numerous examples and case studies, author Ric Messier discusses: The evolving nature of information securityThe risks, rewards, and security considerations when implementing SaaS, cloud computing and VoIP Social media and security risks in the enterprise The risks and rewards of allowing remote connectivity and accessibility to the enterprise network
Discusses the risks associated with technologies such as social media, voice over IP (VoIP) and cloud computing and provides guidance on how to manage that risk through policy changes and technical solutionsPresents a detailed look at the risks and rewards associated with cloud computing and storage as well as software as a service (SaaS) and includes pertinent case studiesExplores the risks associated with the use of social media to the enterprise networkCovers the bring-your-own-device(BYOD) trend, including policy considerations and technical requirements"

Modern systems are an intertwined mesh of human process, physical security, and technology. Attackers are aware of this, commonly leveraging a weakness in one form of security to gain control over an otherwise protected operation. To expose these weaknesses, we need a single unified model that can be used to describe all aspects of the system on equal terms. Designing Secure Systems takes a theory-based approach to concepts underlying all forms of systems - from padlocks, to phishing, to enterprise software architecture. We discuss how weakness in one part of a system creates vulnerability in another, all the while applying standards and frameworks used in the cybersecurity world. Our goal: to analyze the security of the entire system - including people, processes, and technology - using a single model. We begin by describing the core concepts of access, authorization, authentication, and exploitation. We then break authorization down into five interrelated components and describe how these aspects apply to physical, human process, and cybersecurity. Lastly, we discuss how to operate a secure system based on the NIST Cybersecurity Framework (CSF) concepts of "identify, protect, detect, respond, and recover." Other topics covered in this book include the NIST National Vulnerability Database (NVD), MITRE Common Vulnerability Scoring System (CVSS), Microsoft's Security Development Lifecycle (SDL), and the MITRE ATT&CK Framework.

Mobile devices are ubiquitous; therefore, mobile device forensics is absolutely critical. Whether for civil or criminal investigations, being able to extract evidence from a mobile device is essential. This book covers the technical details of mobile devices and transmissions, as well as forensic methods for extracting evidence. There are books on specific issues like Android forensics or iOS forensics, but there is not currently a book that covers all the topics covered in this book. Furthermore, it is such a critical skill that mobile device forensics is the most common topic the Author is asked to teach to law enforcement. This is a niche that is not being adequately filled with current titles. An In-Depth Guide to Mobile Device Forensics is aimed towards undergraduates and graduate students studying cybersecurity or digital forensics. It covers both technical and legal issues, and includes exercises, tests/quizzes, case studies, and slides to aid comprehension.

Reviews IoT software architecture and middleware, data processing and management, security, privacy and reliability, architectures, protocols, technologies, algorithms, and smart objects, sensors, and actuators Explores IoT as it applies to energy, including energy efficiency and management, intelligent energy management, smart energy through blockchain and energy-efficient/aware routing/scheduling challenges and issues Examines IoT as it applies to healthcare including biomedical image and signal analysis, and disease prediction and diagnosis Examines IoT as it applies to smart industry including architecture, blockchain, and Industry 4.0 Discusses different ways to create a better IoT network or IoT platform

The insertion of communication networks in feedback control loops complicates analysis and synthesis of cyber-physical systems (CPSs), and network-induced uncertainties may degrade system control performance. Thus, this book researches networked delay compensation and event-triggered control approaches for a series of CPSs subject to network-induced uncertainties. The authors begin with an introduction to the concepts and challenges of CPSs, followed by an overview of networked control approaches and event-triggered control strategies in CPSs. Then, networked delay compensation and event-triggered control approaches are proposed for CPSs with network communication delay, data dropout, signal quantization, and event-triggered communication. More specifically, networked delay compensation approaches are proposed for linear/nonlinear networked controlled plants with time-varying and random network communication delays and data dropouts. To reduce computational burden and network communication loads in CPSs, event-triggered control, self-triggered control, co-design of event-triggered control and quantized control techniques, and event-triggered disturbance rejection control approaches are also presented. This book is an essential text for researchers and engineers interested in cybersecurity, networked control, and CPSs. It would also prove useful for graduate students in the fields of science, engineering, and computer science.

This book introduces a generic and systematic design-time/run-time methodology for handling the dynamic nature of modern embedded systems, without adding large safety margins in the design. The techniques introduced can be utilized on top of most existing static mapping methodologies to deal effectively with dynamism and to increase drastically their efficiency. This methodology is based on the concept of system scenarios, which group system behaviors that are similar from a multi-dimensional cost perspective, such as resource requirements, delay, and energy consumption. Readers will be enabled to design systems capable to adapt to current inputs, improving system quality and/or reducing cost, possibly learning on-the-fly during execution. Provides an effective solution to deal with dynamic system design Includes a broad survey of the state-of-the-art approaches in this domain Enables readers to design for substantial cost improvements (e.g. energy reductions), by exploiting system scenarios Demonstrates how the methodology has been applied effectively on various, real design problems in the embedded system context

Provides insight into the skill set that requires leveraging strength to move further to act as a good data analyst Discusses how big data along with deep learning holds the potential to significantly increase data understanding and in turn, helps to make decisions Covers the numerous potential applications in healthcare, education, communications, media, and the entertainment industry Offers innovative platforms for integrating big data and deep learning Presents issues related to adequate data storage, sematic indexing, data tagging, and fast information retrieval from big data

This book offers a comprehensive overview of basic communication and networking technologies. It focuses on emerging technologies, such as Software-Defined Network (SDN)-based ad hoc networks, 5G, Machine Learning, and Deep Learning solutions for communication and networking, Cloud Computing, etc. It also includes discussions on practical and innovative applications, including Network Security, Smart Cities, e-health, and Intelligent Systems. Future Trends in 5G and 6G: Challenges, Architecture, and Applications addresses several key issues in SDN energy-efficient systems, the Internet of Things, Big Data, Cloud Computing and Virtualization, Machine Learning, Deep Learning, Cryptography, and 6G wireless technology and its future. It provides students, researchers, and practicing engineers with an expert guide to the fundamental concepts, challenges, architecture, applications, and state-of-the-art developments in communication and networking.

Introducing strong foundations to practical Cyber-Physical Systems Leveraging CPS for pandemic affected society Ensuring Secured and Privacy aware CPS for Sensitive Data in a pandemic situation Providing methodologies to deploy CPS in industries affect by a pandemic

This book provides comprehensive coverage of Network-on-Chip (NoC) security vulnerabilities and state-of-the-art countermeasures, with contributions from System-on-Chip (SoC) designers, academic researchers and hardware security experts. Readers will gain a clear understanding of the existing security solutions for on-chip communication architectures and how they can be utilized effectively to design secure and trustworthy systems.

The opportunistic network is an emerging and recent area of research. To make this research area more adaptable for practical and industrial use, there is a need to further investigate several research challenges in all aspects of opportunistic networks. Therefore, Opportunistic Networks: Fundamentals, Applications and Emerging Trends provides theoretical, algorithmic, simulation, and implementation-based research developments related to fundamentals, applications, and emerging research trends in opportunistic networks. The book follows a theoretical approach to describe fundamentals to beginners and incorporates a practical approach depicting the implementation of real-life applications to intermediate and advanced readers. This book is beneficial for academicians, researchers, developers, and engineers who work in or are interested in the fields related to opportunistic networks, delay tolerant networks, and intermittently connected ad hoc networks. This book also serves as a reference book for graduate and postgraduate courses in computer science, computer engineering, and information technology streams.

This book provides comprehensive coverage of the recent advances in symbolic analysis techniques for design automation of nanometer VLSI systems. The presentation is organized in parts of fundamentals, basic implementation methods and applications for VLSI design. Topics emphasized include statistical timing and crosstalk analysis, statistical and parallel analysis, performance bound analysis and behavioral modeling for analog integrated circuits . Among the recent advances, the Binary Decision Diagram (BDD) based approaches are studied in depth. The BDD-based hierarchical symbolic analysis approaches, have essentially broken the analog circuit size barrier.
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This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit. By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people's behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them. It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.

"CUDA Fortran for Scientists and Engineers" shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran.

To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand the target GPU architecture, identify computationally intensive parts of the code, and modify the code to manage the data and parallelism and optimize performance. All of this is done in Fortran, without having to rewrite in another language. Each concept is illustrated with actual examples so you can immediately evaluate the performance of your code in comparison.
Leverage the power of GPU computing with PGI s CUDA Fortran compilerGain insights from members of the CUDA Fortran language development teamIncludes multi-GPU programming in CUDA Fortran, covering both peer-to-peer and message passing interface (MPI) approachesIncludes full source code for all the examples and several case studies Download source code and slides from the book's companion website"

The Art of Timing Closure is written using a hands-on approach to describe advanced concepts and techniques using Multi-Mode Multi-Corner (MMMC) for an advanced ASIC design implementation. It focuses on the physical design, Static Timing Analysis (STA), formal and physical verification. The scripts in this book are based on Cadence (R) Encounter System (TM). However, if the reader uses a different EDA tool, that tool's commands are similar to those shown in this book. The topics covered are as follows: Data Structures Multi-Mode Multi-Corner Analysis Design Constraints Floorplan and Timing Placement and Timing Clock Tree Synthesis Final Route and Timing Design Signoff Rather than go into great technical depth, the author emphasizes short, clear descriptions which are implemented by references to authoritative manuscripts. It is the goal of this book to capture the essence of physical design and timing analysis at each stage of the physical design, and to show the reader that physical design and timing analysis engineering should be viewed as a single area of expertise. This book is intended for anyone who is involved in ASIC design implementation -- starting from physical design to final design signoff. Target audiences for this book are practicing ASIC design implementation engineers and students undertaking advanced courses in ASIC design.

This book examines research topics in IoT and Cloud and Fog computing. The contributors address major issues and challenges in IoT-based solutions proposed for the Cloud. The authors discuss Cloud smart and energy efficient services in applications such as healthcare, traffic, and farming systems. Targeted readers are from varying disciplines who are interested in designing and deploying the Cloud applications. The book can be helpful to Cloud-based IoT service providers, Cloud-based IoT service consumers, and Cloud service developers in general for getting the state-of-the-art knowledge in the emerging IoT area. The book also provides a strong foundation for researchers to advance further in this domain. Presents a variety of research related to IoT and Cloud computing; Provides the industry with new and innovative operational ideas; Pertinent to academics, researchers, and practitioners around the world.

Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book: Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions. Points to the solutions provided by machine learning to optimize the grids within a smart city set-up. Discusses relevant IoE design principles and architecture. Helps to automate various services in smart cities for energy management. Includes case studies to show the effectiveness of the discussed schemes.

As technology continues to advance and the interconnection of various devices makes our lives easier, it also puts us at further risk of privacy and security threats. Phones can connect to household devices to help set alarms, turn on or off the lights, and even preheat ovens. The Internet of Things (IoT) is this symbiotic interplay of smart devices that collect data and make intelligent decisions. However, the lack of an intrinsic security measure within IoT makes it especially vulnerable to privacy and security threats. Blockchain and IoT Integration highlights how Blockchain, an encrypted, distributed computer filing system, can be used to help protect IoT against such privacy and security breaches. The merger of IoT and blockchain technology is a step towards creating a verifiable, secure, and permanent method of recording data processed by "smart" machines. The text explores the platforms and applications of blockchain-enabled IoT as well as helps clarify how to strengthen the IoT security found in healthcare systems as well as private homes. Other highlights of the book include: Overview of the blockchain architecture Blockchain to secure IoT data Blockchain to secure drug supply chain and combat counterfeits Blockchain IoT concepts for smart grids, smart cities, and smart homes A biometric-based blockchain enabled payment system IoT for smart healthcare monitoring systems