This book is designed to help requirements engineers prepare for the Certified Professional for Requirements Engineering Foundation Level exam as defined by the IREB. Requirements engineering tasks have become increasingly complex. In order to ensure a high level of knowledge and competency among requirements engineers, the International Requirements Engineering Board (IREB) developed a standardized qualification called the Certified Professional for Requirements Engineering (CPRE). The certification defines the practical skills of a requirements engineer on various training levels. This book is designed for self-study and covers the curriculum for the Certified Professional for Requirements Engineering Foundation Level exam as defined by the IREB. The 2nd edition has been thoroughly revised and is aligned with the curriculum Version 2.2 of the IREB. In addition, some minor corrections to the 1st edition have been included. About IREB: The mission of the IREB is to contribute to the standardization of further education in the fields of business analysis and requirements engineering by providing syllabi and examinations, thereby achieving a higher level of applied requirements engineering. The IRE Board is comprised of a balanced mix of independent, internationally recognized experts in the fields of economy, consulting, research, and science. The IREB is a non-profit corporation. For more information visit www.certified-re.com.

The text covers important algorithm design techniques, such as greedy algorithms, dynamic programming, and divide-and-conquer, and gives applications to contemporary problems. Techniques including Fast Fourier transform, KMP algorithm for string matching, CYK algorithm for context free parsing and gradient descent for convex function minimization are discussed in detail. The book's emphasis is on computational models and their effect on algorithm design. It gives insights into algorithm design techniques in parallel, streaming and memory hierarchy computational models. The book also emphasizes the role of randomization in algorithm design, and gives numerous applications ranging from data-structures such as skip-lists to dimensionality reduction methods.

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.

Computational Frameworks: Systems, Models and Applications provides an overview of advanced perspectives that bridges the gap between frontline research and practical efforts. It is unique in showing the interdisciplinary nature of this area and the way in which it interacts with emerging technologies and techniques. As computational systems are a dominating part of daily lives and a required support for most of the engineering sciences, this book explores their usage (e.g. big data, high performance clusters, databases and information systems, integrated and embedded hardware/software components, smart devices, mobile and pervasive networks, cyber physical systems, etc.).

This book presents the different challenges of secure processor architecture design for architects working in industry who want to add security features to their designs as well as graduate students interested in research on architecture and hardware security. It educates readers about how the different challenges have been solved in the past and what are the best practices, i.e., the principles, for design of new secure processor architectures. Based on the careful review of past work by many computer architects and security researchers, readers also will come to know the five basic principles needed for secure processor architecture design. The book also presents existing research challenges and potential new research directions. Finally, it presents numerous design suggestions, as well as discussing pitfalls and fallacies that designers should avoid. With growing interest in computer security and the protection of the code and data which execute on commodity computers, the amount of hardware security features in today's processors has increased significantly over the recent years. No longer of just academic interest, security features inside processors have been embraced by industry as well, with a number of commercial secure processor architectures available today. This book gives readers insights into the principles behind the design of academic and commercial secure processor architectures. Secure processor architecture research is concerned with exploring and designing hardware features inside computer processors, features which can help protect confidentiality and integrity of the code and data executing on the processor. Unlike traditional processor architecture research that focuses on performance, efficiency, and energy as the first-order design objectives, secure processor architecture design has security as the first-order design objective (while still keeping the others as important design aspects that need to be considered).

With recent changes in multicore and general-purpose computing on graphics processing units, the way parallel computers are used and programmed has drastically changed. It is important to provide a comprehensive study on how to use such machines written by specialists of the domain. The book provides recent research results in high-performance computing on complex environments, information on how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems, detailed studies on the impact of applying heterogeneous computing practices to real problems, and applications varying from remote sensing to tomography. The content spans topics such as Numerical Analysis for Heterogeneous and Multicore Systems; Optimization of Communication for High Performance Heterogeneous and Hierarchical Platforms; Efficient Exploitation of Heterogeneous Architectures, Hybrid CPU+GPU, and Distributed Systems; Energy Awareness in High-Performance Computing; and Applications of Heterogeneous High-Performance Computing. Covers cutting-edge research in HPC on complex environments, following an international collaboration of members of the ComplexHPC Explains how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems Twenty-three chapters and over 100 illustrations cover domains such as numerical analysis, communication and storage, applications, GPUs and accelerators, and energy efficiency

John Maeda is one of the world's preeminent thinkers on technology and design, and in How to Speak Machine, he offers a set of simple laws that govern not only the computers of today, but the unimaginable machines of the future. Machines are already more powerful than we can comprehend, and getting more powerful at an exponential pace. Once set in motion, algorithms never tire. And when a program's size, speed and endlessness combine with its ability to learn and transform itself, the outcome can be unpredictable and dangerous. Take the seemingly instant transformation of Microsoft's chatbot into a hate-spewing racist, or how crime-predicting algorithms reinforce racial bias. How To Speak Machine provides a coherent framework for today's product designers, business leaders and policymakers to grasp this brave new world. Drawing on his wide-ranging experience from engineering to computer science to design, Maeda shows how businesses and individuals can identify opportunities afforded by technology to make world-changing and inclusive products while avoiding the pitfalls inherent to the medium.

Graphs are among the most important abstract data types in computer science, and the algorithms that operate on them are critical to modern life. Graphs have been shown to be powerful tools for modeling complex problems because of their simplicity and generality. Graph algorithms are one of the pillars of mathematics, informing research in such diverse areas as combinatorial optimization, complexity theory, and topology. Algorithms on graphs are applied in many ways in today's world - from Web rankings to metabolic networks, from finite element meshes to semantic graphs. The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance. Graph Algorithms in the Language of Linear Algebra is the first book to cover graph algorithms accessible to engineers and scientists not trained in computer science but having a strong linear algebra background, enabling them to quickly understand and apply graph algorithms. It also covers array-based graph algorithms, showing readers how to express canonical graph algorithms using a highly elegant and efficient array notation and how to tap into the large range of tools and techniques that have been built for matrices and tensors; parallel array-based algorithms, demonstrating with examples how to easily implement parallel graph algorithms using array-based approaches, which enables readers to address much larger graph problems; and array-based theory for analyzing graphs, providing a template for using array-based constructs to develop new theoretical approaches for graph analysis.

Electrical Engineering Modeling for Reliability Analysis Markov Modeling for Reliability, Maintainability, Safety, and Supportability Analyses of Complex Computer Systems IEEE Press Series on Engineering of Complex Computer Systems Phillip A. Laplante and Alexander D. Stoyen, Series Editors Markov modeling has long been accepted as a fundamental and powerful technique for the fault tolerance analysis of mission-critical applications. However, the elaborate computations required have often made Markov modeling too time-consuming to be of practical use on these complex systems. With this hands-on tool, designers can use the Markov modeling technique to analyze the safety, reliability, maintainability, and cost-effectiveness factors in the full range of complex systems in use today. Featuring groundbreaking simulation software and a comprehensive reference manual, Modeling for Reliability Analysis helps system designers surmount the mathematical computations that have previously prevented effective reliability analysis. The text and software compose a valuable self-study tool that is complete with detailed explanations, examples, and a library of Markov models that can be used for experiments and as derivations for new simulation models. The book details how these analyses are conducted, while providing hands-on instructions on how to develop reliability models for the full range of system configurations. Computer-Aided Rate Modeling and Simulation (CARMS) software is an integrated modeling tool that includes a diagram-based environment for model setup, a spreadsheet-like interface for data entry, an expert system link for automatic model construction, and an interactive graphic interfacefor displaying simulation results.

Kickstart your emotion analysis journey with this hands-on, step-by-step guide to data science success Key Features * Discover the ins and outs of the end-to-end emotional analysis workflow * Explore the use of various ML models to derive meaningful insights from all sorts of data * Hone your craft by building and tweaking complex emotion analysis models in practical projects Book Description The AI winter has long thawed, but many organizations are still failing to harness the power of machine learning (ML). If you want to tap that potential and add value to your own business with cutting-edge emotion analysis, you've found what you need in this trusty guide. In Machine Learning for Emotion Analysis, you'll take your foundational data science skills and grow them in the exciting realm of emotion analysis. With its practical approach, you'll be equipped with everything you need to give your company a clear insight into what your customers are thinking. This no-nonsense guide jumps right into the practicalities of emotion analysis, teaching you how to preprocess data, build a serviceable dataset, and ensure top-notch data quality. Once you're set up for success, we get hands-on with complex ML techniques. This is where you go from the intermediate to the advanced, covering deep neural networks, support vector machines, conditional probabilities, and more, as you experience the full breadth of possibilities with emotion analysis. The book finally rounds out with a couple of in-depth use cases - a sort of sandbox for you to experiment with your newly acquired skill set. By the end of this book, you'll be ready to present yourself as a valuable asset to any organization that takes data science seriously. What you will learn * Distinguish between sentiment analysis and emotion analysis * Master the art of data preprocessing and ensure high-quality input * Expand your use of data sources through data transformation * Build models that employ cutting-edge deep learning techniques * Discover how best to tune your models' hyperparameters * Explore the use of KNN, SVM, and DNNs for advanced use cases * Build APIs and integrate your models into existing solutions * Practice your new skills by working on real-world scenarios Who This Book Is For This book is for data scientists and Python developers who want to gain insights into what people are saying about their product, company, brand, governorship, and more. Basic knowledge of machine learning and Python programming knowledge is necessary to grasp the concepts covered.

High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to Volume 1, the techniques included here explain how to use processors and coprocessors with the same programming - illustrating the most effective ways to combine Xeon Phi coprocessors with Xeon and other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as biomed, genetics, finance, manufacturing, imaging, and more. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Learn from dozens of new examples and case studies illustrating "success stories" demonstrating not just the features of Xeon-powered systems, but also how to leverage parallelism across these heterogeneous systems.

System-on-chip (SoC) technology is revolutionizing the way computers are designed and used, driving down their cost and making them more pervasive than ever before. However, it's extremely challenging for designers to get their SoC designs right the first time. ARM System Architecture, Second Edition gives system designers an authoritative, inside perspective on SoC design -- and on ARM, the world's #1, fastest-growing SoC platform for mobile phones and information appliances. The insights in this book will be crucial to every system designer and ARM licensee seeking to build more effective SoC designs -- and get them to market more quickly. KEY TOPICS: In contrast to most ARM documentation, this book explains not only what ARM is, but why -- and how you can leverage it most effectively. Expert system designer and ARM specialist Steve Furber introduces the key design challenges associated with SoC systems, including memory hierarchy, caches, memory management, on-chip debug, and production test. Next, he presents state-of-the-art ARM-based solutions for each key problem. Furber reviews the entire ARM processor family, helping designers choose the most appropriate solutions; and covers both the ARM and Thumb programming models, providing real-world guidance for developing applications more quickly and effectively. The book includes a helpful review of the fundamentals of computer architecture, as well as valuable coverage of related topics such as digital signal processing and asynchronous design. MARKET:

This book describes the Splash 2 computing system as designed and built at the Supercomputing Research Center. This is a novel attached processor using Xilinx 4010 FPGAs as its processing elements and whose application programming language is VHDL. This is the first publication that details the complete Splash 2 project -- the hardware and software systems, the architecture and their implementations, and the design process by which the architecture evolved from an earlier version machine. This text allows you to understand why the machine has been engineered in the way it has. In addition to the description of the machine, several applications are described in detail, permitting the reader to gain an understanding of the capabilities and the limitations of this kind of computing device.
The Splash 2 program is significant for two reasons. First, Splash 2 is part of a complete computer system that achieves supercomputer like performance on a number of different applications. The second significant aspect is that this large system is capable of performing real computations on real problems. In order to understand what happens when the application programmer is permitted to design the processor architecture of the machine that execute his programs, it is necessary to see the system as a whole. This book looks in-depth at one of the handful of data points in the design space of this new kind of machine.

"Modeling Enterprise Architecture with TOGAF" explains everything you need to know to effectively model enterprise architecture with The Open Group Architecture Framework (TOGAF), the leading EA standard. This solution-focused reference presents key techniques and illustrative examples to help you model enterprise architecture.

This book describes the TOGAF standard and its structure, from the architecture transformation method to governance, and presents enterprise architecture modeling practices with plenty of examples of TOGAF deliverables in the context of a case study.

Although widespread and growing quickly, enterprise architecture is delicate to manage across all its dimensions. Focusing on the architecture transformation method, TOGAF provides a wide framework, which covers the repository, governance, and a set of recognized best practices. The examples featured in this book were realized using the open source Modelio tool, which includes extensions for TOGAF.
Includes intuitive summaries of the complex TOGAF standard to let you effectively model enterprise architectureUses practical examples to illustrate ways to adapt TOGAF to the needs of your enterprise Provides model examples with Modelio, a free modeling tool, letting you exercise TOGAF modeling immediately using a dedicated tool Combines existing modeling standards with TOGAF

"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"

"Network and System Security" provides focused coverage of network and system security technologies. It explores practical solutions to a wide range of network and systems security issues. Chapters are authored by leading experts in the field and address the immediate and long-term challenges in the authors respective areas of expertise. Coverage includes building a secure organization, cryptography, system intrusion, UNIX and Linux security, Internet security, intranet security, LAN security; wireless network security, cellular network security, RFID security, and more.
Chapters contributed by leaders in the field covering foundational and practical aspects of system and network security, providing a new level of technical expertise not found elsewhereComprehensive and updated coverage of the subject area allows the reader to put current technologies to workPresents methods of analysis and problem solving techniques, enhancing the reader s grasp of the material and ability to implement practical solutions"

This proven textbook guides readers to a thorough understanding of the theory and design of operational amplifiers (OpAmps). The core of the book presents systematically the design of operational amplifiers, classifying them into a periodic system of nine main overall configurations, ranging from one gain stage up to four or more stages. This division enables circuit designers to recognize quickly, understand, and choose optimal configurations. Characterization of operational amplifiers is given by macro models and error matrices, together with measurement techniques for their parameters. Definitions are given for four types of operational amplifiers depending on the grounding of their input and output ports. Many famous designs are evaluated in depth, using a carefully structured approach enhanced by numerous figures. In order to reinforce the concepts introduced and facilitate self-evaluation of design skills, the author includes problems with detailed solutions, as well as simulation exercises.

"Heterogeneous Computing with OpenCL "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. 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, this book will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. The authors explore memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. Intended to support a parallel programming course, "Heterogeneous Computing with OpenCL" includes detailed examples throughout, plus additional online exercises and other supporting materials.
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 architecturesAddresses a range of fundamental programming techniques, with multiple examples and case studies that demonstrate OpenCL extensions for a variety of hardware platforms

This book constitutes the proceedings of the 33rd International Conference on Architecture of Computing Systems, ARCS 2020, held in Aachen, Germany, in May 2020.* The 12 full papers in this volume were carefully reviewed and selected from 33 submissions. 6 workshop papers are also included. ARCS has always been a conference attracting leading-edge research outcomes in Computer Architecture and Operating Systems, including a wide spectrum of topics ranging from embedded and real-time systems all the way to large-scale and parallel systems. The selected papers focus on concepts and tools for incorporating self-adaptation and self-organization mechanisms in high-performance computing systems. This includes upcoming approaches for runtime modifications at various abstraction levels, ranging from hardware changes to goal changes and their impact on architectures, technologies, and languages. *The conference was canceled due to the COVID-19 pandemic.

How can we provide guarantees of behaviours for autonomous systems such as driverless cars? This tutorial text, for professionals, researchers and graduate students, explains how autonomous systems, from intelligent robots to driverless cars, can be programmed in ways that make them amenable to formal verification. The authors review specific definitions, applications and the unique future potential of autonomous systems, along with their impact on safer decisions and ethical behaviour. Topics discussed include the use of rational cognitive agent programming from the Beliefs-Desires-Intentions paradigm to control autonomous systems and the role model-checking in verifying the properties of this decision-making component. Several case studies concerning both the verification of autonomous systems and extensions to the framework beyond the model-checking of agent decision-makers are included, along with complete tutorials for the use of the freely-available verifiable cognitive agent toolkit Gwendolen, written in Java.

In today's workplace, computer and cybersecurity professionals must understand both hardware and software to deploy effective security solutions. This book introduces readers to the fundamentals of computer architecture and organization for security, and provides them with both theoretical and practical solutions to design and implement secure computer systems. Offering an in-depth and innovative introduction to modern computer systems and patent-pending technologies in computer security, the text integrates design considerations with hands-on lessons learned to help practitioners design computer systems that are immune from attacks. Studying computer architecture and organization from a security perspective is a new area. There are many books on computer architectures and many others on computer security. However, books introducing computer architecture and organization with security as the main focus are still rare. This book addresses not only how to secure computer components (CPU, Memory, I/O, and network) but also how to secure data and the computer system as a whole. It also incorporates experiences from the author's recent award-winning teaching and research. The book also introduces the latest technologies, such as trusted computing, RISC-V, QEMU, cache security, virtualization, cloud computing, IoT, and quantum computing, as well as other advanced computing topics into the classroom in order to close the gap in workforce development. The book is chiefly intended for undergraduate and graduate students in computer architecture and computer organization, as well as engineers, researchers, cybersecurity professionals, and middleware designers.

For courses in engineering and technical management System architecture is the study of early decision making in complex systems. This text teaches how to capture experience and analysis about early system decisions, and how to choose architectures that meet stakeholder needs, integrate easily, and evolve flexibly. With case studies written by leading practitioners, from hybrid cars to communications networks to aircraft, this text showcases the science and art of system architecture.