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Books > Computing & IT > Computer hardware & operating systems > Computer architecture & logic design > Parallel processing
Edsger Wybe Dijkstra (1930-2002) was one of the most influential researchers in the history of computer science, making fundamental contributions to both the theory and practice of computing. Early in his career, he proposed the single-source shortest path algorithm, now commonly referred to as Dijkstra's algorithm. He wrote (with Jaap Zonneveld) the first ALGOL 60 compiler, and designed and implemented with his colleagues the influential THE operating system. Dijkstra invented the field of concurrent algorithms, with concepts such as mutual exclusion, deadlock detection, and synchronization. A prolific writer and forceful proponent of the concept of structured programming, he convincingly argued against the use of the Go To statement. In 1972 he was awarded the ACM Turing Award for "fundamental contributions to programming as a high, intellectual challenge; for eloquent insistence and practical demonstration that programs should be composed correctly, not just debugged into correctness; for illuminating perception of problems at the foundations of program design." Subsequently he invented the concept of self-stabilization relevant to fault-tolerant computing. He also devised an elegant language for nondeterministic programming and its weakest precondition semantics, featured in his influential 1976 book A Discipline of Programming in which he advocated the development of programs in concert with their correctness proofs. In the later stages of his life, he devoted much attention to the development and presentation of mathematical proofs, providing further support to his long-held view that the programming process should be viewed as a mathematical activity. In this unique new book, 31 computer scientists, including five recipients of the Turing Award, present and discuss Dijkstra's numerous contributions to computing science and assess their impact. Several authors knew Dijkstra as a friend, teacher, lecturer, or colleague. Their biographical essays and tributes provide a fascinating multi-author picture of Dijkstra, from the early days of his career up to the end of his life.
Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. Applying Integration Techniques and Methods in Distributed Systems is a critical scholarly publication that defines the current state of distributed systems, determines further goals, and presents architectures and service frameworks to achieve highly integrated distributed systems and presents solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting topics such as multimedia, programming languages, and smart environments, this book is ideal for system administrators, integrators, designers, developers, researchers, and academicians.
Recent years have witnessed the rise of analysis of real-world massive and complex phenomena in graphs; to efficiently solve these large-scale graph problems, it is necessary to exploit high performance computing (HPC), which accelerates the innovation process for discovery and invention of new products and procedures in network science. Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing: Emerging Research and Opportunities is a critical scholarly resource that examines trends, challenges, and collaborative processes in emerging fields within complex network analysis. Featuring coverage on a broad range of topics such as high-performance computing, big data, network science, and accelerated network traversal, this book is geared towards data analysts, researchers, students in information communication technology (ICT), program developers, and academics.
As the future of software development in a global environment continues to be influenced by the areas of service oriented architecture (SOA) and cloud computing, many legacy applications will need to migrate these environments to take advantage of the benefits offered by the service environment. Migrating Legacy Applications: Challenges in Service Oriented Architecture and Cloud Computing Environments presents a closer look at the partnership between service oriented architecture and cloud computing environments while analyzing potential solutions to challenges related to the migration of legacy applications. This reference is essential for students and university scholars alike.
In recent years, most applications deal with constraint decision-making systems as problems are based on imprecise information and parameters. It is difficult to understand the nature of data based on applications and it requires a specific model for understanding the nature of the system. Further research on constraint decision-making systems in engineering is required. Constraint Decision-Making Systems in Engineering derives and explores several types of constraint decisions in engineering and focuses on new and innovative conclusions based on problems, robust and efficient systems, and linear and non-linear applications. Covering topics such as fault detection, data mining techniques, and knowledge-based management, this premier reference source is an essential resource for engineers, managers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.
Present day sophisticated, adaptive, and autonomous (to a certain degree) robotic technology is a radically new stimulus for the cognitive system of the human learner from the earliest to the oldest age. It deserves extensive, thorough, and systematic research based on novel frameworks for analysis, modelling, synthesis, and implementation of CPSs for social applications. Cyber-Physical Systems for Social Applications is a critical scholarly book that examines the latest empirical findings for designing cyber-physical systems for social applications and aims at forwarding the symbolic human-robot perspective in areas that include education, social communication, entertainment, and artistic performance. Highlighting topics such as evolinguistics, human-robot interaction, and neuroinformatics, this book is ideally designed for social network developers, cognitive scientists, education science experts, evolutionary linguists, researchers, and academicians.
This book is a celebration of Leslie Lamport's work on concurrency, interwoven in four-and-a-half decades of an evolving industry: from the introduction of the first personal computer to an era when parallel and distributed multiprocessors are abundant. His works lay formal foundations for concurrent computations executed by interconnected computers. Some of the algorithms have become standard engineering practice for fault tolerant distributed computing - distributed systems that continue to function correctly despite failures of individual components. He also developed a substantial body of work on the formal specification and verification of concurrent systems, and has contributed to the development of automated tools applying these methods. Part I consists of technical chapters of the book and a biography. The technical chapters of this book present a retrospective on Lamport's original ideas from experts in the field. Through this lens, it portrays their long-lasting impact. The chapters cover timeless notions Lamport introduced: the Bakery algorithm, atomic shared registers and sequential consistency; causality and logical time; Byzantine Agreement; state machine replication and Paxos; temporal logic of actions (TLA). The professional biography tells of Lamport's career, providing the context in which his work arose and broke new grounds, and discusses LaTeX - perhaps Lamport's most influential contribution outside the field of concurrency. This chapter gives a voice to the people behind the achievements, notably Lamport himself, and additionally the colleagues around him, who inspired, collaborated, and helped him drive worldwide impact. Part II consists of a selection of Leslie Lamport's most influential papers. This book touches on a lifetime of contributions by Leslie Lamport to the field of concurrency and on the extensive influence he had on people working in the field. It will be of value to historians of science, and to researchers and students who work in the area of concurrency and who are interested to read about the work of one of the most influential researchers in this field.
Computation and Storage in the Cloud is the first comprehensive
and systematic work investigating the issue of computation and
storage trade-off in the cloud in order to reduce the overall
application cost. Scientific applications are usually computation
and data intensive, where complex computation tasks take a long
time for execution and the generated datasets are often terabytes
or petabytes in size. Storing valuable generated application
datasets can save their regeneration cost when they are reused, not
to mention the waiting time caused by regeneration. However, the
large size of the scientific datasets is a big challenge for their
storage. By proposing innovative concepts, theorems and algorithms,
this book will help bring the cost down dramatically for both cloud
users and service providers to run computation and data intensive
scientific applications in the cloud. Covers cost models and
benchmarking that explain the necessary tradeoffs for both cloud
providers and usersDescribes several novel strategies for storing
application datasets in the cloudIncludes real-world case studies
of scientific research applications Describes several novel strategies for storing application datasets in the cloud Includes real-world case studies of scientific research applications
This book contains the papers presented at the Parallel
Computational Fluid Dynamics 1998 Conference.
As software and computer hardware grows in complexity, networks have grown to match. The increasing scale, complexity, heterogeneity, and dynamism of communication networks, resources, and applications has made distributed computing systems brittle, unmanageable, and insecure. Internet and Distributed Computing Advancements: Theoretical Frameworks and Practical Applications is a vital compendium of chapters on the latest research within the field of distributed computing, capturing trends in the design and development of Internet and distributed computing systems that leverage autonomic principles and techniques. The chapters provided within this collection offer a holistic approach for the development of systems that can adapt themselves to meet requirements of performance, fault tolerance, reliability, security, and Quality of Service (QoS) without manual intervention.
This book precisely formulates and simplifies the presentation of Instruction Level Parallelism (ILP) compilation techniques. It uniquely offers consistent and uniform descriptions of the code transformations involved. Due to the ubiquitous nature of ILP in virtually every processor built today, from general purpose CPUs to application-specific and embedded processors, this book is useful to the student, the practitioner and also the researcher of advanced compilation techniques. With an emphasis on fine-grain instruction level parallelism, this book will also prove interesting to researchers and students of parallelism at large, in as much as the techniques described yield insights that go beyond superscalar and VLIW (Very Long Instruction Word) machines compilation and are more widely applicable to optimizing compilers in general. ILP techniques have found wide and crucial application in Design Automation, where they have been used extensively in the optimization of performance as well as area and power minimization of computer designs.
In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich, is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines, and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and, in some cases, Fortran. This book is also ideal for practitioners and programmers.
This book provides a comprehensive analysis of the most important topics in parallel computation. It is written so that it may be used as a self-study guide to the field, and researchers in parallel computing will find it a useful reference for many years to come. The first half of the book consists of an introduction to many fundamental issues in parallel computing. The second half provides lists of P-complete- and open problems. These lists will have lasting value to researchers in both industry and academia. The lists of problems, with their corresponding remarks, the thorough index, and the hundreds of references add to the exceptional value of this resource. While the exciting field of parallel computation continues to expand rapidly, this book serves as a guide to research done through 1994 and also describes the fundamental concepts that new workers will need to know in coming years. It is intended for anyone interested in parallel computing, including senior level undergraduate students, graduate students, faculty, and people in industry. As an essential reference, the book will be needed in all academic libraries.
A state-of-the-art guide for the implementation of distributed simulation technology.
Massively Parallel Systems (MPSs) with their scalable computation and storage space promises are becoming increasingly important for high-performance computing. The growing acceptance of MPSs in academia is clearly apparent. However, in industrial companies, their usage remains low. The programming of MPSs is still the big obstacle, and solving this software problem is sometimes referred to as one of the most challenging tasks of the 1990's. The 1994 working conference on "Programming Environments for Massively Parallel Systems" was the latest event of the working group WG 10.3 of the International Federation for Information Processing (IFIP) in this field. It succeeded the 1992 conference in Edinburgh on "Programming Environments for Parallel Computing." The research and development work discussed at the conference addresses the entire spectrum of software problems including virtual machines which are less cumbersome to program; more convenient programming models; advanced programming languages, and especially more sophisticated programming tools; but also algorithms and applications.
This volume gives an overview of the state-of-the-art with respect to the development of all types of parallel computers and their application to a wide range of problem areas.
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