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Parallel Processing for Scientific Computing

Parallel Processing for Scientific Computing

£77.00

Part of Software, Environments and Tools

  • Date Published: March 2007
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Paperback
  • isbn: 9780898716191

£ 77.00
Paperback

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About the Authors
  • Parallel Processing for Scientific Computing is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, scientists, and computer scientists focus on to make parallel processing effective for scientific problems. It is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth looks at applications that require parallel computing for scaling to solve larger and more realistic models that can advance science and engineering. In sum, this is an up-to-date reference for researchers and application developers on the state of the art in scientific computing. It also serves as an excellent overview and introduction, especially for students interested in computational modeling and simulation.

    • Up-to-date reference for researchers and application developers on the state of the art in scientific computing
    • Suitable as an introduction for graduate and senior-level undergraduate students
    • First book with this breadth of coverage for 10 years
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    Product details

    • Date Published: March 2007
    • format: Paperback
    • isbn: 9780898716191
    • length: 420 pages
    • dimensions: 253 x 174 x 19 mm
    • weight: 0.864kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    List of Figures
    List of Tables
    Preface
    1. Frontiers of Scientific Computing. An Overview
    Part I. Performance Modeling, Analysis and Optimization
    2. Performance Analysis. From Art to Science
    3. Approaches to Architecture-Aware Parallel Scientific Computation
    4. Achieving High Performance on the BlueGene/L Supercomputer
    5. Performance Evaluation and Modeling of Ultra-Scale Systems
    Part II. Parallel Algorithms and Enabling Technologies
    6. Partitioning and Load Balancing
    7. Combinatorial Parallel and Scientific Computing
    8. Parallel Adaptive Mesh Refinement
    9. Parallel Sparse Solvers, Preconditioners, and Their Applications
    10. A Survey of Parallelization Techniques for Multigrid Solvers
    11. Fault Tolerance in Large-Scale Scientific Computing
    Part III. Tools and Frameworks for Parallel Applications
    12. Parallel Tools and Environments. A Survey
    13. Parallel Linear Algebra Software
    14. High-Performance Component Software Systems
    15. Integrating Component-Based Scientific Computing Software
    Part IV. Applications of Parallel Computing
    16. Parallel Algorithms for PDE-Constrained Optimization
    17. Massively Parallel Mixed-Integer Programming
    18. Parallel Methods and Software for Multicomponent Simulations
    19. Parallel Computational Biology
    20. Opportunities and Challenges for Parallel Computing in Science and Engineering
    Index.

  • Editors

    Michael A. Heroux, Sandia National Laboratory
    Michael A. Heroux is the Solvers Project Leader at Sandia National Laboratory; his work focuses on new algorithm development and robust parallel implementation of solver components. He leads development of the Trilinos Project, an effort to provide solution methods in a state-of-the-art software framework. He also maintains an active interest in the interaction between scientific/engineering applications and high-performance computer architectures.

    Padma Raghavan, Pennsylvania State University
    Padma Raghavan is a Professor in the Department of Computer Science and Engineering at Pennsylvania State University. Her research interests include parallel and distributed computing, sparse matrix graph techniques and their applications, and software environments and component architectures for large-scale computational materials science.

    Horst D. Simon, Lawrence Berkeley National Laboratory
    Horst D. Simon is Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory. His recursive spectral bisection algorithm is regarded as a breakthrough in parallel algorithms for unstructured computations, and he was honored for his algorithm research efforts with the 1988 Gordon Bell Prize for parallel processing research.

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