Skip to main content
SpringerLink
Log in
Book cover

Numerical Solution of Partial Differential Equations on Parallel Computers

  • Conference proceedings
  • © 2006

Overview

Editors:
  1. Are Magnus Bruaset

    1. Simula Research Laboratory, Lysaker, Fornebu, Norway

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Aslak Tveito

    1. Simula Research Laboratory, Lysaker, Fornebu, Norway

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computational Science and Engineering (LNCSE, volume 51)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (13 papers)

  1. Front Matter

    Pages I-XII
    Download chapter PDF

  2. Parallel Computing

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Parallel Programming Models Applicable to Cluster Computing and Beyond

      • Ricky A. Kendall, Masha Sosonkina, William D. Gropp, Robert W. Numrich, Thomas Sterling
      Pages 3-54

    3. Partitioning and Dynamic Load Balancing for the Numerical Solution of Partial Differential Equations

      • James D. Teresco, Karen D. Devine, Joseph E. Flaherty
      Pages 55-88

    4. Graphics Processor Units: New Prospects for Parallel Computing

      • Martin Rumpf, Robert Strzodka
      Pages 89-132

  3. Parallel Algorithms

    1. Front Matter

      Pages 133-133
      Download chapter PDF

    2. Domain Decomposition Techniques

      • Luca Formaggia, Marzio Sala, Fausto Saleri
      Pages 135-163

    3. Parallel Geometric Multigrid

      • Frank Hülsemann, Markus Kowarschik, Marcus Mohr, Ulrich Rüde
      Pages 165-208

    4. Parallel Algebraic Multigrid Methods — High Performance Preconditioners

      • Ulrike Meier Yang
      Pages 209-236

    5. Parallel Mesh Generation

      • Nikos Chrisochoides
      Pages 237-264

  4. Parallel Software Tools

    1. Front Matter

      Pages 265-265
      Download chapter PDF

    2. The Design and Implementation of hypre, a Library of Parallel High Performance Preconditioners

      • Robert D. Falgout, Jim E. Jones, Ulrike Meier Yang
      Pages 267-294

    3. Parallelizing PDE Solvers Using the Python Programming Language

      • Xing Cai, Hans Petter Langtangen
      Pages 295-325

    4. Parallel PDE-Based Simulations Using the Common Component Architecture

      • Lois Curfman McInnes, Benjamin A. Allan, Robert Armstrong, Steven J. Benson, David E. Bernholdt, Tamara L. Dahlgren et al.
      Pages 327-381

  5. Parallel Applications

    1. Front Matter

      Pages 383-383
      Download chapter PDF

    2. Full-Scale Simulation of Cardiac Electrophysiology on Parallel Computers

      • Xing Cai, Glenn Terje Lines
      Pages 385-411

    3. Developing a Geodynamics Simulator with PETSc

      • Matthew G. Knepley, Richard F. Katz, Barry Smith
      Pages 413-438

    4. Parallel Lattice Boltzmann Methods for CFD Applications

      • Carolin Körner, Thomas Pohl, Ulrich Rüde, Nils Thürey, Thomas Zeiser
      Pages 439-466

  6. Back Matter

    Pages 467-487
    Download chapter PDF
Back to top

Keywords

About this book

Since the dawn of computing, the quest for a better understanding of Nature has been a driving force for technological development. Groundbreaking achievements by great scientists have paved the way from the abacus to the supercomputing power of today. When trying to replicate Nature in the computer’s silicon test tube, there is need for precise and computable process descriptions. The scienti?c ?elds of Ma- ematics and Physics provide a powerful vehicle for such descriptions in terms of Partial Differential Equations (PDEs). Formulated as such equations, physical laws can become subject to computational and analytical studies. In the computational setting, the equations can be discreti ed for ef?cient solution on a computer, leading to valuable tools for simulation of natural and man-made processes. Numerical so- tion of PDE-based mathematical models has been an important research topic over centuries, and will remain so for centuries to come. In the context of computer-based simulations, the quality of the computed results is directly connected to the model’s complexity and the number of data points used for the computations. Therefore, computational scientists tend to ?ll even the largest and most powerful computers they can get access to, either by increasing the si e of the data sets, or by introducing new model terms that make the simulations more realistic, or a combination of both. Today, many important simulation problems can not be solved by one single computer, but calls for parallel computing.

Editors and Affiliations

  • Simula Research Laboratory, Lysaker, Fornebu, Norway

    Are Magnus Bruaset, Aslak Tveito

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation