Encyclopedia of Parallel Computing

This book constitutes the refereed proceedings of the 8th International Conference on Parallel Computing Technologies, PaCT 2005, held in Krasnoyarsk, Russia in September 2005.The 38 revised full pape

"THE LANGUAGE OF COMPUTING AND COMMUNICATIONS AT YOUR FINGERTIPS Derived from the world-renowned McGraw-Hill Dictionary of Scientific and Technical Terms, Sixth Edition, this vital reference offers a

Contains more than seven hundred entries that cover all aspects of computer science and the history of computing.

Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing in

This book sets out the principles of parallel computing in a way which will be useful to student and potential user alike. It includes coverage of both conventional and neural computers. The content of the book is arranged hierarchically. It explains why, where and how parallel computing is used; the fundamental paradigms employed in the field; how systems are programmed or trained; technical aspects including connectivity and processing element complexity; and how system performance is estimated (and why doing so is difficult). The penultimate chapter of the book comprises a set of case studies of archetypal parallel computers, each study written by an individual closely connected with the system in question. The final chapter correlates the various aspects of parallel computing into a taxonomy of systems.

CUDA is now the dominant language used for programming GPUs, one of the most exciting hardware developments of recent decades. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a HPC facility. As a result, CUDA is increasingly important in scientific and technical computing across the whole STEM community, from medical physics and financial modelling to big data applications and beyond. This unique book on CUDA draws on the author's passion for and long experience of developing and using computers to acquire and analyse scientific data. The result is an innovative text featuring a much richer set of examples than found in any other comparable book on GPU computing. Much attention has been paid to the C++ coding style, which is compact, elegant and efficient. A code base of examples and supporting material is available online, which readers can build on for their own projects.

The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing par

This book constitutes the thoroughly refereed post-conference proceedings of the 28th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2015, held in Raleigh, NC, USA, in

With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputin

The two volumes LNCS 8805 and 8806 constitute the thoroughly refereed post-conference proceedings of 18 workshops held at the 20th International Conference on Parallel Computing, Euro-Par 2014, in Por

This book constitutes the thoroughly refereed post-conference proceedings of the 26th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2013, held in Tokyo, Japan, in Sept

Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Acce

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 Accelera

Despite five decades of research, parallel computing remains an exotic, frontier technology on the fringes of mainstream computing. Its much-heralded triumph over sequential computing has yet to mater

This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy

Designed for researchers, engineers, IT professionals, and graduate students in parallel and cloud computing, this volume covers the state of the art in cloud computing theory and practice. It spans t

The arrival and popularity of multi-core processors has sparked a renewed interest in the development of parallel programs. Similarly, the availability of low-cost microprocessors and sensors has generated a great interest in embedded real-time programs. This book provides students and programmers whose backgrounds are in traditional sequential programming with the opportunity to expand their capabilities into parallel, embedded, real-time and distributed computing. It also addresses the theoretical foundation of real-time scheduling analysis, focusing on theory that is useful for actual applications. Written by award-winning educators at a level suitable for undergraduates and beginning graduate students, this book is the first truly entry-level textbook in the subject. Complete examples allow readers to understand the context in which a new concept is used, and enable them to build and run the examples, make changes, and observe the results.

Avicenna’s Physics is the very first volume that he wrote when he began his monumental encyclopedia of science and philosophy, The Healing. Avicenna’s reasons for beginning with Phy

An analytical overview of the state of the art, open problems, and future trends in heterogeneous parallel and distributed computing This book provides an overview of the ongoing academic research, d

This book constitutes the thoroughly refereed post-conference proceedings of the 21th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2008, held in Edmonton, Canada, in

This book constitutes the thoroughly refereed post-conference proceedings of the 20th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2007, held in Urbana, IL, USA, in O

In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo

In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo

This comprehensive encyclopedia covers all aspects of computer science, engineering, and technology. Its scope of work is structured using the ACM Computing Classification System (CCS) first published

This book addresses the high performance computing of the Discrete Element Model (DEM). It is a comprehensive presentation of parallel implementation of the DEM on three popular parallel computing pla

This work characterizes the latest research on the use of quality of service (QoS) in grid computing, for academicians, engineers, IT professionals, and researchers in fields such as parallel and dist

This book provides an overview of and essential insights on invasive computing. Pursuing a comprehensive approach, it addresses proper concepts, invasive language constructs, and the principles of inv

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Computing, Euro-Par 2008, held in Las Palmas de Gran Canaria, Spain, in August 2008.The 86 revised paper

Solving problems in parallel and distributed computing through the use of bio-inspired techniques. Recent years have seen a surge of interest in computational methods patterned after natural phenomena

PVM is a software package that enables the computer user to define a networked heterogeneous collection of serial, parallel, and vector computers to function as one large computer. Written by the tea

The synergy between Artificial Intelligence (AI) and the Internet of Things (IoT) is shaping the future of technology and opening a world of unprecedented possibilities. Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share with readers their ideas about how to implement technical advances, application areas for intelligent systems, and development of new services and smart devices connected to the Internet through a variety of wireless technologies. Parallel to this, new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power are opening the way to new domains, services, and business models beyond the traditional mobile Internet. These new areas in turn come with various requirements in terms of reliability, quality of service, and energy efficiency. In Artificial Intelligence of Things readers learn about the challenges and requiremen

We are now confronted with a new type of uncanny experience, an uncanny evoked by parallel processing, aggregate data, and cloud-computing. The digital uncanny does not erase the uncanny feeling we ex

We are now confronted with a new type of uncanny experience, an uncanny evoked by parallel processing, aggregate data, and cloud-computing. The digital uncanny does not erase the uncanny feeling we ex

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algo

The advent of multi-core architectures and cloud-computing has brought parallel programming into the mainstream of software development. Unfortunately, writing scalable parallel programs using traditi

A team of Russian researchers follow their beginning graduate textbook on computational technologies with this more advanced one on computational technologies for parallel computing systems. They emph

This book provides a detailed overview on the use of global optimization and parallel computing in microwave tomography techniques. The book focuses on techniques that are based on global optimization

Simulation and Behavioral Modeling of Analogue Systems focuses on numerical simulations of analogue systems by use of functional behavioral models, presenting a MATLAB toolbox optimized for NVIDIA GPU