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An introduction to parallel and vect...

Lefton, L. (1960-)

An introduction to parallel and vector scientific computing /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	004.3/5
書名/作者:	An introduction to parallel and vector scientific computing // Ronald W. Shonkwiler, Lew Lefton.
其他題名:	An Introduction to Parallel & Vector Scientific Computation
作者:	Shonkwiler, Ronald W.,
其他作者:	Lefton, L.
面頁冊數:	1 online resource (xv, 288 pages) : : digital, PDF file(s).
附註:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
標題:	Parallel processing (Electronic computers) - Congresses.
標題:	Vector processing (Computer science)
ISBN:	9780511617935 (ebook)
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1017/CBO9780511617935

An introduction to parallel and vector scientific computing /
Shonkwiler, Ronald W.,1942-

An introduction to parallel and vector scientific computing /An Introduction to Parallel & Vector Scientific ComputationRonald W. Shonkwiler, Lew Lefton. - 1 online resource (xv, 288 pages) :digital, PDF file(s). - Cambridge texts in applied mathematics ;41. - Cambridge texts in applied mathematics ;35..

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

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.

ISBN: 9780511617935 (ebook)Subjects--Topical Terms:

386175
Parallel processing (Electronic computers)
--Congresses.

LC Class. No.: QA76.58 / .S545 2006

Dewey Class. No.: 004.3/5

An introduction to parallel and vector scientific computing /
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520 $a 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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