Parallel Scientific Computing and Optimization

Advances and Applications

  • Raimondas Čiegis
  • David Henty
  • Bo Kågström
  • Julius Žilinskas

Part of the Springer Optimization and Its Applications book series (SOIA, volume 27)

Table of contents

  1. Front Matter
    Pages I-XXIII
  2. Parallel Algorithms for Matrix Computations

    1. Front Matter
      Pages 1-1
    2. Alexander Jakusšev, Raimondas Čiegis, Inga Laukaitytė, Vyacheslav Trofimov
      Pages 25-36
    3. Richard L. Muddle, Jonathan W. Boyle, Milan D. Mihajlović, Matthias Heil
      Pages 37-46
    4. Christophe Denis, Raphael Couturier, Fabienne Jézéquel
      Pages 47-56
  3. Parallel Optimization

    1. Front Matter
      Pages 67-67
    2. Kristian Woodsend, Jacek Gondzio
      Pages 83-92
    3. Sergėjus Ivanikovas, Ernestas Filatovas, Julius Žilinskas
      Pages 103-112
  4. Management of Parallel Programming Models and Data

    1. Front Matter
      Pages 113-113
    2. Ilian T. Todorovm, Ian J. Bush, Andrew R. Porter
      Pages 125-132
    3. Michał Piotrowski
      Pages 133-143
    4. Andreas Grothey, Jonathan Hogg, Kristian Woodsend, Marco Colombo, Jacek Gondzio
      Pages 145-156
    5. Roy Smits, Michael Kramer, Ben Stappers, Andrew Faulkner
      Pages 157-165
  5. Parallel Scientific Computing in Industrial Applications

    1. Front Matter
      Pages 167-167
    2. Raimondas Čiegis, Francisco Gaspar, Carmen Rodrigo
      Pages 169-180

About this book


Parallel Scientific Computing and Optimization introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. This book presents 23 self-contained chapters, including surveys, written by distinguished researchers in the field of parallel computing. Each chapter is devoted to some aspects of the subject: parallel algorithms for matrix computations, parallel optimization, management of parallel programming models and data, with the largest focus on parallel scientific computing in industrial applications.

Key features include:

* construction and analysis of parallel algorithms for linear algebra and optimization problems;

* different aspects of parallel architectures, including distributed memory computers with multicore processors;

* a wide range of industrial applications: parallel simulation of flows through oil filters as well as in porous and gas media, jet aerodynamics, heat conduction in electrical cables, nonlinear optics processes in tapered lasers, and molecular and cell dynamics.

This volume is intended for scientists and graduate students specializing in computer science and applied mathematics who are engaged in parallel scientific computing.


Analysis Matrix algorithm algorithms computer science global optimization model modeling modelling molecular dynamics multidimensional scaling optimization programming scientific computing simulation

Authors and affiliations

  • Raimondas Čiegis
    • 1
  • David Henty
    • 2
  • Bo Kågström
    • 3
  • Julius Žilinskas
    • 4
  1. 1.Department of Mathematical ModellingVilnius Gediminas Technical UniversityLithuania
  2. 2.University of EdinburghUnited Kingdom
  3. 3.Umeå UniversitySweden
  4. 4.Vilnius Gediminas Technical University and Institute of Mathematics and InformaticsLithuania

Bibliographic information

  • DOI
  • Copyright Information Springer New York 2009
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-09706-0
  • Online ISBN 978-0-387-09707-7
  • Series Print ISSN 1931-6828
  • About this book