9780521864787 - An Introduction to Parallel and Vector Scientific Computation Hardback: 41 (Cambridge Texts in Applied Mathematics, Series Number 41) de Shonkwiler; Lefton (18 resultados)

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Condición: New. In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context. Series: Cambridge Texts in Applied Mathematics. Num Pages: 308 pages, 10 tables 120 exercises. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 228 x 152 x 21. Weight in Grams: 620. . 2006. Illustrated. hardcover. . . . .

Condición: New. In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context. Series: Cambridge Texts in Applied Mathematics. Num Pages: 308 pages, 10 tables 120 exercises. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 228 x 152 x 21. Weight in Grams: 620. . 2006. Illustrated. hardcover. . . . . Books ship from the US and Ireland.

Condición: Hervorragend. Zustand: Hervorragend | Seiten: 308 | Sprache: Englisch | Produktart: Bücher | In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

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Hardcover. Condición: new. Hardcover. 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. In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context. Topics include direct and iterative methods for solving linear systems, numerical methods for the eigenvector/eigenvalue problem and applications to Monte Carlo methods. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Hardcover. Condición: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. &Uumlber den AutorRonald W. Shonkwiler is a Professor in the School of Mathematics at the Georgia Institute of Technology. He has authored or co-authored over 50 research papers in areas of functional analysis, mathematical biology, ima.

Hardcover. Condición: new. Hardcover. 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. In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context. Topics include direct and iterative methods for solving linear systems, numerical methods for the eigenvector/eigenvalue problem and applications to Monte Carlo methods. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.