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This book introduces the basic concepts of parallel and vector computing in the context of an introduction to numerical methods. It contains chapters on parallel and vector matrix multiplication and solution of linear systems by direct and iterative methods. It is suitable for advanced undergraduate and beginning graduate courses in computer science, applied mathematics, and engineering. Ideally, students will have access to a parallel or Vector computer, but the material can be studied profitably in any case. * Gives a modern overview of scientific computing including parallel an vector computation * Introduces numerical methods for both ordinary and partial differential equations * Has considerable discussion of both direct and iterative methods for linear systems of equations, including parallel and vector algorithms * Covers most of the main topics for a first course in numerical methods and can serve as a text for this course

Parallel processing (Electronic computers). --- Vector processing (Computer science).

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Parallel processing (Electronic computers) --- Vector processing (Computer science)

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Parallel processing (Electronic computers) --- Vector processing (Computer science) --- Congresses.

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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 methods.

Parallel processing (Electronic computers) --- Vector processing (Computer science)

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Parallel processing (Electronic computers) --- Congresses --- Vector processing (Computer science) --- Congresses. --- Parallel processing (Electronic computers) - Congresses. --- Vector processing (Computer science) - Congresses.