Encyclopedia of Parallel Computing

From its earliest days, the Fortran programming language has been designed with computing efficiency in mind. The latest standard, Fortran 2008, incorporates a host of modern features, including object-orientation, array operations, user-defined types, and provisions for parallel computing. This tutorial guide shows Fortran programmers how to apply these features in twenty-first-century style: modular, concise, object-oriented, and resource-efficient, using multiple processors. It offers practical real-world examples of interfacing to C, memory management, graphics and GUIs, and parallel computing using MPI, OpenMP, and coarrays. The author also analyzes several numerical algorithms and their implementations and illustrates the use of several open source libraries. Full source code for the examples is available on the book's website.

From its earliest days, the Fortran programming language has been designed with computing efficiency in mind. The latest standard, Fortran 2008, incorporates a host of modern features, including object-orientation, array operations, user-defined types, and provisions for parallel computing. This tutorial guide shows Fortran programmers how to apply these features in twenty-first-century style: modular, concise, object-oriented, and resource-efficient, using multiple processors. It offers practical real-world examples of interfacing to C, memory management, graphics and GUIs, and parallel computing using MPI, OpenMP, and coarrays. The author also analyzes several numerical algorithms and their implementations and illustrates the use of several open source libraries. Full source code for the examples is available on the book's website.

In this 1991 book, Hilbers discusses the general case of how to use processors simultaneously in order to solve a single problem rather than any specific application, and develops a theory independent of particular architectures. He starts by introducing distributed computing with graph theory, and considers processor networks and their price/performance ratios. He goes on to look at obtaining homogeneous distributions of work over networks and considers examples. Finally he discusses message routing within a processor network. This is intended to be a fundamental treatment of the relevant subjects and is aimed at computer scientists and graduate students in computer science who have experience with parallel processing: it will also be useful to others interested in processor networks.

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

Originally published in 1993, this book was the first to offer a comprehensive review of large eddy simulations (LES) - the history, state of the art, and promising directions for research. Among topics covered are fundamentals of LES; LES of incompressible, compressible, and reacting flows; LES of atmospheric, oceanic, and environmental flows; and LES and massivelt parallel computing. The book grew out of an international workshop that, for the first time, brought together leading researchers in engineering and geophysics to discuss developments and applications of LES models in their respective fields. It will be of value to anyone with an interest in turbulence modelling.

First published in 1976, this monograph presents an exposition of some of the more important theoretical and computational techniques that have been developed for the determination and interpretation of molecular wave functions. Although a comprehensive theory of the electronic structure and bonding in molecules had been developed by 1960, only with the advent of the electronic computer in the late 1950s did it become possible to perform accurate non-empirical calculations for molecules of chemical interest; indeed, much of the subsequent evolution of the theory has occurred in parallel with the development of computing machines and techniques.

This book, first published in 2000, explores the exciting field of complexity. It features in-depth coverage of important theoretical areas, including fractals, chaos, non-linear dynamics, artificial life and self-organization. It also provides overviews of complexity in several applied areas, including parallel computation, control systems, neural systems and ecosystems. Some of the properties that best characterize complex systems, including algorithmic richness, non-linearity and abundant interactions between components are examined. In this way the book draws out themes, especially the ideas of connectivity and natural computation, that reveal deep, underlying similarities between phenomena that have formerly been treated as completely distinct. The idea of natural computation is particularly rich in fresh approaches applicable to both biology and computing. Analogies such as the DNA code as life's underlying program, or organisms as automata, are very compelling. Conversely, biolo

Methods from contact and symplectic geometry can be used to solve highly non-trivial nonlinear partial and ordinary differential equations without resorting to approximate numerical methods or algebraic computing software. This book explains how it's done. It combines the clarity and accessibility of an advanced textbook with the completeness of an encyclopedia. The basic ideas that Lie and Cartan developed at the end of the nineteenth century to transform solving a differential equation into a problem in geometry or algebra are here reworked in a novel and modern way. Differential equations are considered as a part of contact and symplectic geometry, so that all the machinery of Hodge-deRham calculus can be applied. In this way a wide class of equations can be tackled, including quasi-linear equations and Monge-Ampere equations (which play an important role in modern theoretical physics and meteorology).

Complex fluid flows are encountered widely in nature, in living beings and in engineering practice. These flows often involve both geometric and dynamic complexity and present problems that are difficult to analyse because of their wide range of length and time scales, as well as their geometric configuration. This book describes some computational techniques and modelling strategies for analysing and predicting complex transport phenomena. It summarizes advances in the context of a pressure-based algorithm. Among methods discussed are discretization schemes for treating convection and pressure, parallel computing, multigrid methods, and composite, multiblock techniques. With respect to physical modelling, the book addresses issues of turbulence closure and multiscale, multiphase transport from an engineering viewpoint. Both fundamental and practical issues are considered, along with the relative merits of competing approaches. Numerous examples are given throughout the text. Mechanica

A gentle introduction to advanced topics such as parallel computing, multigrid methods, and special methods for systems of PDEs. The goal of all chapters is to ‘compute’ solutions to problems, hence a

This book presents an easy-to-read discussion of domain decomposition algorithms, their implementation and analysis. The relationship between domain decomposition and multigrid methods is carefully explained at an elementary level, and discussions of the implementation of domain decomposition methods on massively parallel super computers are also included. All algorithms are fully described and explained, and a mathematical framework for the analysis and complete understanding of the methods is also carefully developed. In addition, numerous numerical examples are included to demonstrate the behaviour of this important class of numerical methods. This book is ideal for graduate students about to embark on a career in computational science. It will also be a valuable resource for all those interested in parallel computing and numerical computational methods.

Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly large amounts of data. In parallel, advances in computing have led to

This book, first published in 2000, explores the exciting field of complexity. It features in-depth coverage of important theoretical areas, including fractals, chaos, non-linear dynamics, artificial life and self-organization. It also provides overviews of complexity in several applied areas, including parallel computation, control systems, neural systems and ecosystems. Some of the properties that best characterize complex systems, including algorithmic richness, non-linearity and abundant interactions between components are examined. In this way the book draws out themes, especially the ideas of connectivity and natural computation, that reveal deep, underlying similarities between phenomena that have formerly been treated as completely distinct. The idea of natural computation is particularly rich in fresh approaches applicable to both biology and computing. Analogies such as the DNA code as life's underlying program, or organisms as automata, are very compelling. Conversely, biolo

Complex fluid flows are encountered widely in nature, in living beings and in engineering practice. These flows often involve both geometric and dynamic complexity and present problems that are difficult to analyse because of their wide range of length and time scales, as well as their geometric configuration. This book describes some computational techniques and modelling strategies for analysing and predicting complex transport phenomena. It summarizes advances in the context of a pressure-based algorithm. Among methods discussed are discretization schemes for treating convection and pressure, parallel computing, multigrid methods, and composite, multiblock techniques. With respect to physical modelling, the book addresses issues of turbulence closure and multiscale, multiphase transport from an engineering viewpoint. Both fundamental and practical issues are considered, along with the relative merits of competing approaches. Numerous examples are given throughout the text. Mechanica

In this 1991 book, Hilbers discusses the general case of how to use processors simultaneously in order to solve a single problem rather than any specific application, and develops a theory independent of particular architectures. He starts by introducing distributed computing with graph theory, and considers processor networks and their price/performance ratios. He goes on to look at obtaining homogeneous distributions of work over networks and considers examples. Finally he discusses message routing within a processor network. This is intended to be a fundamental treatment of the relevant subjects and is aimed at computer scientists and graduate students in computer science who have experience with parallel processing: it will also be useful to others interested in processor networks.

This book constitutes the proceedings of the 14th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2017, held in Hefei, China, in October 2017.The 9 full papers and 10 shor

McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cog

Foreword by Bjarne Stroustrup Software is generally acknowledged to be the single greatest obstacle preventing mainstream adoption of massively-parallel computing. While sequential applications are ro

Since the publication of the first edition, parallel computing technology has gained considerable momentum. A large proportion of this has come from the improvement in VLSI techniques, offering one to

Communications of ACMInternet ResearchIEEE Transactions on Parallel and Distributed SystemsParallel ComputingIEEE Transactions on ComputersACM Transactions on Computer Systems

"Vector Models for Data-Parallel Computing "describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It

This book constitutes the proceedings of the workshops of the 23rd International Conference on Parallel and Distributed Computing, Euro-Par 2017, held in Santiago de Compostela. Spain in August 2017

This book provides a systematic, foundational introduction to automatic alignment of parallel texts, a family of essential corpus analysis techniques for computing and learning the mappings between co

GAME DEVELOPMENT WITH MICROSOFT DIRECTCOMPUTE teaches the theories behind parallel computing and computing on the graphics card, and provides hands-on examples of real tasks that could be solved using

July 6-8, 1994 * the Massachusetts Institute of Technology The field of artificial life has recently emerged through the interaction of research in biology, physics, parallel computing, artificial in

Computational Fluid Dynamics (CFD) is one of the most important applications for high-performance computing, setting the pace for developments in scientific computing. Anyone who wants to design a new

McClelland and Rumelhart's "Parallel Distributed Processing "was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and c