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Numerical Computations with GPUs

  • Book
  • © 2014

Overview

Editors:
  1. Volodymyr Kindratenko

    1. National Center for Supercomputing Applications, University of Illinois, Urbana, USA

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  • Enriches understanding of numerical methods adapted for GPU architecture

  • Clarifies the difference between implementation details for individual methods

  • Provides reusable code fragments that can be used as-is or modified for user-specific applications

  • Includes supplementary material: sn.pub/extras

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Table of contents (18 chapters)

  1. Fast Fourier Transform and Localized n-Body Problems

    1. Fast Fourier Transform (FFT) on GPUs

      • Yash Ukidave, Gunar Schirner, David Kaeli
      Pages 339-361

    2. A Highly Efficient FFT Using Shared-Memory Multiplexing

      • Yi Yang, Huiyang Zhou
      Pages 363-377

    3. Increasing Parallelism and Reducing Thread Contentions in Mapping Localized N-Body Simulations to GPUs

      • Bharat Sukhwani, Martin C. Herbordt
      Pages 379-405
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Keywords

About this book

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.

Reviews

From the book reviews:

“This book attempts to provide some guidance for researchers who develop HPC codes and want to run them on GPU-based systems. … The intended readership consists of people who already have a certain amount of experience in working with GPUs … . For readers with such a background, it will prove to be useful reading.” (Kai Diethelm, Computing Reviews, November, 2014)

Editors and Affiliations

  • National Center for Supercomputing Applications, University of Illinois, Urbana, USA

    Volodymyr Kindratenko

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