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Numerical Computations with GPUs

  • Volodymyr Kindratenko

Table of contents

  1. Front Matter
    Pages i-x
  2. Linear Algebra

    1. Front Matter
      Pages 1-1
    2. Jack Dongarra, Mark Gates, Azzam Haidar, Jakub Kurzak, Piotr Luszczek, Stanimire Tomov et al.
      Pages 3-28
    3. Li-Wen Chang, Wen-mei W. Hwu
      Pages 29-44
    4. M. Graham Lopez, Mitchel D. Horton
      Pages 45-67
    5. William J. Brouwer, Pierre-Yves Taunay
      Pages 69-86
    6. Antonino Tumeo, Nitin Gawande, Oreste Villa
      Pages 87-101
    7. Zbigniew Koza, Maciej Matyka, Łukasz Mirosław, Jakub Poła
      Pages 103-121
  3. Differential Equations

    1. Front Matter
      Pages 123-123
    2. Karsten Ahnert, Denis Demidov, Mario Mulansky
      Pages 125-157
    3. Dominik Göddeke, Dimitri Komatitsch, Matthias Möller
      Pages 183-206
    4. Yiannis Cotronis, Elias Konstantinidis, Nikolaos M. Missirlis
      Pages 207-221
    5. Lídia Kuan, Pedro Tomás, Leonel Sousa
      Pages 223-242
  4. Random Numbers and Monte Carlo Methods

    1. Front Matter
      Pages 243-243
    2. Elise de Doncker, John Kapenga, Rida Assaf
      Pages 273-298
    3. Joanna Wiśniewska, Marek Sawerwain
      Pages 299-318
  5. Fast Fourier Transform and Localized n-Body Problems

    1. Front Matter
      Pages 337-337
    2. Yash Ukidave, Gunar Schirner, David Kaeli
      Pages 339-361
    3. Yi Yang, Huiyang Zhou
      Pages 363-377

About this book

Introduction

This book brings together research on numerical methods adapted for Graphics Processing Units (GPUs). It explains recent efforts to adapt classic numerical methods, including solution of linear equations and FFT, for massively parallel GPU architectures. This volume consolidates recent research and adaptations, covering widely used methods that are at the core of many scientific and engineering computations. Each chapter is written by authors working on a specific group of methods; these leading experts provide mathematical background, parallel algorithms and implementation details leading to reusable, adaptable and scalable code fragments. This book also serves as a GPU implementation manual for many numerical algorithms, sharing tips on GPUs that can increase application efficiency. The valuable insights into parallelization strategies for GPUs are supplemented by ready-to-use code fragments. Numerical Computations with GPUs targets professionals and researchers working in high performance computing and GPU programming. Advanced-level students focused on computer science and mathematics will also find this book useful as secondary text book or reference.

Keywords

Differential equations GPUs Iterative solvers Linear algebra Monte Carlo Numerical methods Parallel algorithms Random number generators

Editors and affiliations

  • Volodymyr Kindratenko
    • 1
  1. 1.National Center for Supercomputing ApplicationsUniversity of IllinoisUrbanaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-06548-9
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-06547-2
  • Online ISBN 978-3-319-06548-9
  • Buy this book on publisher's site