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  3. An Introduction to Parallel and Vector Scientific Computation
  • Cited by 12
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    • Publisher:
      Cambridge University Press
      Publication date:
      December 2009
      August 2006
      ISBN:
      9780511617935
      9780521864787
      9780521683371
      DOI:
      https://doi.org/10.1017/CBO9780511617935
      Dimensions:
      (228 x 152 mm)
      Weight & Pages:
      0.55kg, 308 Pages
      Dimensions:
      (228 x 152 mm)
      Weight & Pages:
      0.432kg, 300 Pages
      • Subjects:
      Mathematics, Differential and Integral Equations, Dynamical Systems and Control Theory, Mathematical Physics, Computer Science, Numerical Analysis and Computational Science, Scientific Computing, Scientific Software
      Series:
      Cambridge Texts in Applied Mathematics (41)
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    • Selected: Digital
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    Subjects:
    Mathematics, Differential and Integral Equations, Dynamical Systems and Control Theory, Mathematical Physics, Computer Science, Numerical Analysis and Computational Science, Scientific Computing, Scientific Software
    Series:
    Cambridge Texts in Applied Mathematics (41)
    Information

    Book description

    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.

    Reviews

    '… in spite of the clear need to present these concepts to a much broader technical audience, there is a perplexing dearth of training material and textbooks in the field, particularly at the introductory level. … it is indeed refreshing to see the publication of the book An Introduction to Parallel and Vector Scientific Computing, written by Ronald W. Shonkwiler and Lew Lefton, both of the Georgia institute of Technology. They have taken the bull by the horns and produced a book that appears to be entirely satisfactory as an introductory textbook for use in such a course.'

    Source: Scientific Programming

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