This book introduces new compilation techniques, using the polyhedron model for the resource-adaptive parallel execution of loop programs on massively parallel processor arrays. The authors show how to compute optimal symbolic assignments and parallel schedules of loop iterations at compile time, for cases where the number of available cores becomes known only at runtime. The compile/runtime symbolic parallelization approach the authors describe reduces significantly the runtime overhead, compared to dynamic or just-in-time compilation. The new, on-demand fault-tolerant loop processing approach described in this book protects loop nests for parallel execution against soft errors.

Coding Approaches to Fault Tolerance in Combinational and Dynamic Systems describes coding approaches for designing fault-tolerant systems, i.e., systems that exhibit structured redundancy that enables them to distinguish between correct and incorrect results or between valid and invalid states. Since redundancy is expensive and counter-intuitive to the traditional notion of system design, the book focuses on resource-efficient methodologies that avoid excessive use of redundancy by exploiting the algorithmic/dynamic structure of a particular combinational or dynamic system. The first part of Coding Approaches to Fault Tolerance in Combinational and Dynamic Systems focuses on fault-tolerant combinational systems providing a review of von Neumann's classical work on Probabilistic Logics (including some more recent work on noisy gates) and describing the use of arithmetic coding and algorithm-based fault-tolerant schemes in algebraic settings. The second part of the book focuses on fault tolerance in dynamic systems. Coding Approaches to Fault Tolerance in Combinational and Dynamic Systems also discusses how, in a dynamic system setting, one can relax the traditional assumption that the error-correcting mechanism is fault-free by using distributed error correcting mechanisms. The final chapter presents a methodology for fault diagnosis in discrete event systems that are described by Petri net models; coding techniques are used to quickly detect and identify failures. From the Foreword "Hadjicostis has significantly expanded the setting to processes occurring in more general algebraic and dynamic systems... The book responds to the growing need to handle faults in complex digital chips and complex networked systems, and to consider the effects of faults at the design stage rather than afterwards." George Verghese, Massachusetts Institute of Technology Coding Approaches to Fault Tolerance in Combinational and Dynamic Systems will be of interest to both researchers and practitioners in the area of fault tolerance, systems design and control.

This book is written as an introduction to annotated logics. It provides logical foundations for annotated logics, discusses some interesting applications of these logics and also includes the authors' contributions to annotated logics. The central idea of the book is to show how annotated logic can be applied as a tool to solve problems of technology and of applied science. The book will be of interest to pure and applied logicians, philosophers and computer scientists as a monograph on a kind of paraconsistent logic. But, the layman will also take profit from its reading.

This book presents several significant advances in algorithms designed to solve the Do-All problem in distributed message-passing settings under various models of adversity, including processor crashes, asynchrony, message delays, network partitions, and malicious processor behaviors. Upper and lower bounds are presented, demonstrating the extent to which efficiency can be combined with fault-tolerance. This book contains the recent advances in the principles of efficient and fault-tolerant cooperative computing, narrowing the gap between abstract models of dependable network computing and realistic distributed systems.

Parallel and distributed computation has been gaining a great lot of attention in the last decades. During this period, the advances attained in computing and communication technologies, and the reduction in the costs of those technolo gies, played a central role in the rapid growth of the interest in the use of parallel and distributed computation in a number of areas of engineering and sciences. Many actual applications have been successfully implemented in various plat forms varying from pure shared-memory to totally distributed models, passing through hybrid approaches such as distributed-shared memory architectures. Parallel and distributed computation differs from dassical sequential compu tation in some of the following major aspects: the number of processing units, independent local dock for each unit, the number of memory units, and the programming model. For representing this diversity, and depending on what level we are looking at the problem, researchers have proposed some models to abstract the main characteristics or parameters (physical components or logical mechanisms) of parallel computers. The problem of establishing a suitable model is to find a reasonable trade-off among simplicity, power of expression and universality. Then, be able to study and analyze more precisely the behavior of parallel applications."

Derived from industry-training classes that the author teaches at the Embedded Systems Institute at Eindhoven, the Netherlands and at Buskerud University College at Kongsberg in Norway, Systems Architecting: A Business Perspective places the processes of systems architecting in a broader context by juxtaposing the relationship of the systems architect with enterprise and management. This practical, scenario-driven guide fills an important gap, providing systems architects insight into the business processes, and especially into the processes to which they actively contribute. The book uses a simple reference model to enable understanding of the inside of a system in relation to its context. It covers the impact of tool selection and brings balance to the application of the intellectual tools versus computer-aided tools. Stressing the importance of a clear strategy, the authors discuss methods and techniques that facilitate the architect's contribution to the strategy process. They also give insight into the needs and complications of harvesting synergy, insight that will help establish an effective synergy-harvesting strategy. The book also explores the often difficult relationship between managers and systems architects. Written in an approachable style, the book discusses the breadth of the human sciences and their relevance to systems architecting. It highlights the relevance of human aspects to systems architects, linking theory to practical experience when developing systems architecting competence.

This monograph evolved from my Ph. D dissertation completed at the Laboratory of Computer Science, MIT, during the Summer of 1986. In my dissertation I proposed a pipelined code mapping scheme for array operations on static dataflow architectures. The main addition to this work is found in Chapter 12, reflecting new research results developed during the last three years since I joined McGill University-results based upon the principles in my dissertation. The terminology dataflow soft ware pipelining has been consistently used since publication of our 1988 paper on the argument-fetching dataflow architecture model at McGill University 43]. In the first part of this book we describe the static data flow graph model as an operational model for concurrent computation. We look at timing considerations for program graph execution on an ideal static dataflow computer, examine the notion of pipe lining, and characterize its performance. We discuss balancing techniques used to transform certain graphs into fully pipelined data flow graphs. In particular, we show how optimal balancing of an acyclic data flow graph can be formulated as a linear programming problem for which an optimal solution exists. As a major result, we show the optimal balancing problem of acyclic data flow graphs is reduceable to a class of linear programming problem, the net work flow problem, for which well-known efficient algorithms exist. This result disproves the conjecture that such problems are computationally hard."

Within the Smart Grid, the combination of automation equipment, communication technology and IT is crucial. Interoperability of devices and systems can be seen as the key enabler of smart grids. Therefore, international initiatives have been started in order to identify interoperability core standards for Smart Grids. IEC 62357, the so called Seamless Integration Architecture, is one of these very core standards, which has been identified by recent Smart Grid initiatives and roadmaps to be essential for building and managing intelligent power systems. The Seamless Integration Architecture provides an overview of the interoperability and relations between further standards from IEC TC 57 like the IEC 61970/61968: Common Information Model - CIM. CIM has proven to be a mature standard for interoperability and engineering; consequently, it is a cornerstone of the IEC Smart Grid Standardization Roadmap. This book provides an overview on how the CIM developed, in which international projects and roadmaps is has already been covered and describes the basic use cases for CIM. This book has been written for both Power Engineers trying to get to know the EMS and business IT part of Smart Grid and for Computer Scientist finding out where ICT technology is applied in EMS and DMS Systems. The book is divided into two parts dealing with the theoretical foundations and a practical part describing tools and use cases for CIM.

This book presents a wide-band and technology independent, SPICE-compatible RLC model for through-silicon vias (TSVs) in 3D integrated circuits. This model accounts for a variety of effects, including skin effect, depletion capacitance and nearby contact effects. Readers will benefit from in-depth coverage of concepts and technology such as 3D integration, Macro modeling, dimensional analysis and compact modeling, as well as closed form equations for the through silicon via parasitics. Concepts covered are demonstrated by using TSVs in applications such as a spiral inductorand inductive-based communication system and bandpass filtering."

Artificial Intelligence for Capital Market throws light on application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book: Features: Showcases artificial intelligence in finance service industry Explains Credit and Risk Analysis Elaborates on cryptocurrencies and blockchain technology Focuses on optimal choice of asset pricing model Introduces Testing of market efficiency and Forecasting in Indian Stock Market This book serves as a reference book for Academicians, Industry Professional, Traders, Finance Mangers and Stock Brokers. It may also be used as textbook for graduate level courses in financial services and financial Analytics.

This book describes analytical models and estimation methods to enhance performance estimation of pipelined multiprocessor systems-on-chip (MPSoCs). A framework is introduced for both design-time and run-time optimizations. For design space exploration, several algorithms are presented to minimize the area footprint of a pipelined MPSoC under a latency or a throughput constraint. A novel adaptive pipelined MPSoC architecture is described, where idle processors are transitioned into low-power states at run-time to reduce energy consumption. Multi-mode pipelined MPSoCs are introduced, where multiple pipelined MPSoCs optimized separately are merged into a single pipelined MPSoC, enabling further reduction of the area footprint by sharing the processors and communication buffers. Readers will benefit from the authors' combined use of analytical models, estimation methods and exploration algorithms and will be enabled to explore billions of design points in a few minutes.

With the fast pace of change in today's business environment, the need to transform organizations into agile enterprises that can respond quickly to change has never been greater. Methods and computer technologies are needed to enable rapid business and system change, and this practical book shows professionals how to achieve this agility. The solution lies in Enterprise Integration (both business and technology integration). For business integration, the book explains how to use enterprise architecture methods to integrate data, processes, locations, people, events and business plans throughout an organization.

The book covers a range of topics dealing with emerging computing technologies which are being developed in response to challenges faced due to scaling CMOS technologies. It provides a sneak peek into the capabilities unleashed by these technologies across the complete system stack, with contributions by experts discussing device technology, circuit, architecture and design automation flows. Presenting a gradual progression of the individual sub-domains and the open research and adoption challenges, this book will be of interest to industry and academic researchers, technocrats and policymakers. Chapters "Innovative Memory Architectures Using Functionality Enhanced Devices" and "Intelligent Edge Biomedical Sensors in the Internet of Things (IoT) Era" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book discusses the implementation of digital circuits by using MCML gates. Although digital circuit implementation is possible with other elements, such as CMOS gates, MCML implementations can provide superior performance in certain applications. This book provides a complete automation methodology for the implementation of digital circuits in MCML and provides an extensive explanation on the technical details of design of MCML. A systematic methodology is presented to build efficient MCML standard-cell libraries, and a complete top-down design flow is shown to implement complex systems using such building blocks.

This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.

Grounded in the user-centered design movement, this book offers a broad consideration of how our civilization has evolved its technical infrastructure for human purpose to help us make sense of the contemporary world of information infrastructure and online existence. The author incorporates historical, cultural and aesthetic approaches to situating information and its underlying technologies across time in the collective, lived experiences of humanity. In today's digital information world, user experience is vital to the success of any product or service. Yet as the user population expands to include us all, designing for people who vary in skills, abilities, preferences and backgrounds is challenging. This book provides an integrated understanding of users, and the methods that have evolved to identify usability challenges, that can facilitate cohesive and earlier solutions. The book treats information creation and use as a core human behavior based on acts of representation and recording that humans have always practiced. It suggests that the traditional ways of studying information use, with their origins in the distinct layers of social science theories and models is limiting our understanding of what it means to be an information user and hampers our efforts at being truly user-centric in design. Instead, the book offers a way of integrating the knowledge base to support a richer view of use and users in design education and evaluation. Understanding Users is aimed at those studying or practicing user-centered design and anyone interested in learning how people might be better integrated in the design of new technologies to augment human capabilities and experiences.

High Performance Computational Methods for Biological Sequence Analysis presents biological sequence analysis using an interdisciplinary approach that integrates biological, mathematical and computational concepts. These concepts are presented so that computer scientists and biomedical scientists can obtain the necessary background for developing better algorithms and applying parallel computational methods. This book will enable both groups to develop the depth of knowledge needed to work in this interdisciplinary field. This work focuses on high performance computational approaches that are used to perform computationally intensive biological sequence analysis tasks: pairwise sequence comparison, multiple sequence alignment, and sequence similarity searching in large databases. These computational methods are becoming increasingly important to the molecular biology community allowing researchers to explore the increasingly large amounts of sequence data generated by the Human Genome Project and other related biological projects. The approaches presented by the authors are state-of-the-art and show how to reduce analysis times significantly, sometimes from days to minutes. High Performance Computational Methods for Biological Sequence Analysis is tremendously important to biomedical science students and researchers who are interested in applying sequence analyses to their studies, and to computational science students and researchers who are interested in applying new computational approaches to biological sequence analyses.

The advent of very large scale integrated circuit technology has enabled the construction of very complex and large interconnection networks. By most accounts, the next generation of supercomputers will achieve its gains by increasing the number of processing elements, rather than by using faster processors. The most difficult technical problem in constructing a supercom puter will be the design of the interconnection network through which the processors communicate. Selecting an appropriate and adequate topological structure of interconnection networks will become a critical issue, on which many research efforts have been made over the past decade. The book is aimed to attract the readers' attention to such an important research area. Graph theory is a fundamental and powerful mathematical tool for de signing and analyzing interconnection networks, since the topological struc ture of an interconnection network is a graph. This fact has been univer sally accepted by computer scientists and engineers. This book provides the most basic problems, concepts and well-established results on the topological structure and analysis of interconnection networks in the language of graph theory. The material originates from a vast amount of literature, but the theory presented is developed carefully and skillfully. The treatment is gen erally self-contained, and most stated results are proved. No exercises are explicitly exhibited, but there are some stated results whose proofs are left to the reader to consolidate his understanding of the material."

This book provides a comprehensive introduction to processing-in-memory (PIM) technology, from its architectures to circuits implementations on multiple memory types and describes how it can be a viable computer architecture in the era of AI and big data. The authors summarize the challenges of AI hardware systems, processing-in-memory (PIM) constraints and approaches to derive system-level requirements for a practical and feasible PIM solution. The presentation focuses on feasible PIM solutions that can be implemented and used in real systems, including architectures, circuits, and implementation cases for each major memory type (SRAM, DRAM, and ReRAM).

Fault-Tolerant Parallel Computation presents recent advances in algorithmic ways of introducing fault-tolerance in multiprocessors under the constraint of preserving efficiency. The difficulty associated with combining fault-tolerance and efficiency is that the two have conflicting means: fault-tolerance is achieved by introducing redundancy, while efficiency is achieved by removing redundancy. This monograph demonstrates how in certain models of parallel computation it is possible to combine efficiency and fault-tolerance and shows how it is possible to develop efficient algorithms without concern for fault-tolerance, and then correctly and efficiently execute these algorithms on parallel machines whose processors are subject to arbitrary dynamic fail-stop errors. The efficient algorithmic approaches to multiprocessor fault-tolerance presented in this monograph make a contribution towards bridging the gap between the abstract models of parallel computation and realizable parallel architectures. Fault-Tolerant Parallel Computation presents the state of the art in algorithmic approaches to fault-tolerance in efficient parallel algorithms. The monograph synthesizes work that was presented in recent symposia and published in refereed journals by the authors and other leading researchers. This is the first text that takes the reader on the grand tour of this new field summarizing major results and identifying hard open problems. This monograph will be of interest to academic and industrial researchers and graduate students working in the areas of fault-tolerance, algorithms and parallel computation and may also be used as a text in a graduate course on parallel algorithmic techniques and fault-tolerance.

Efficient parallel solutions have been found to many problems. Some of them can be obtained automatically from sequential programs, using compilers. However, there is a large class of problems - irregular problems - that lack efficient solutions. IRREGULAR 94 - a workshop and summer school organized in Geneva - addressed the problems associated with the derivation of efficient solutions to irregular problems. This book, which is based on the workshop, draws on the contributions of outstanding scientists to present the state of the art in irregular problems, covering aspects ranging from scientific computing, discrete optimization, and automatic extraction of parallelism. Audience: This first book on parallel algorithms for irregular problems is of interest to advanced graduate students and researchers in parallel computer science.

In Symbolic Analysis for Parallelizing Compilers the author presents an excellent demonstration of the effectiveness of symbolic analysis in tackling important optimization problems, some of which inhibit loop parallelization. The framework that Haghighat presents has proved extremely successful in induction and wraparound variable analysis, strength reduction, dead code elimination and symbolic constant propagation. The approach can be applied to any program transformation or optimization problem that uses properties and value ranges of program names. Symbolic analysis can be used on any transformational system or optimization problem that relies on compile-time information about program variables. This covers the majority of, if not all optimization and parallelization techniques. The book makes a compelling case for the potential of symbolic analysis, applying it for the first time - and with remarkable results - to a number of classical optimization problems: loop scheduling, static timing or size analysis, and dependence analysis. It demonstrates how symbolic analysis can solve these problems faster and more accurately than existing hybrid techniques.

This book provides an introduction to digital storage for consumer electronics. It discusses the various types of digital storage, including emerging non-volatile solid-state storage technologies and their advantages and disadvantages. It discusses the best practices for selecting, integrating, and using storage devices for various applications. It explores the networking of devices into an overall organization that results in always-available home storage combined with digital storage in the cloud to create an infrastructure to support emerging consumer applications and the Internet of Things. It also looks at the role of digital storage devices in creating security and privacy in consumer products.

This second edition focuses on the thought process of digital design and implementation in the context of VLSI and system design. It covers the Verilog 2001 and Verilog 2005 RTL design styles, constructs and the optimization at the RTL and synthesis level. The book also covers the logic synthesis, low power, multiple clock domain design concepts and design performance improvement techniques. The book includes 250 design examples/illustrations and 100 exercise questions. This volume can be used as a core or supplementary text in undergraduate courses on logic design and as a text for professional and vocational coursework. In addition, it will be a hands-on professional reference and a self-study aid for hobbyists.