CUDA Application Design and Development
eBook - ePub

CUDA Application Design and Development

  1. 336 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

CUDA Application Design and Development

Book details
Table of contents
Citations

About This Book

As the computer industry retools to leverage massively parallel graphics processing units (GPUs), this book is designed to meet the needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. CUDA Application Design and Development starts with an introduction to parallel computing concepts for readers with no previous parallel experience, and focuses on issues of immediate importance to working software developers: achieving high performance, maintaining competitiveness, analyzing CUDA benefits versus costs, and determining application lifespan.

The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries.

Using an approach refined in a series of well-received articles at Dr Dobb's Journal, author Rob Farber takes the reader step-by-step from fundamentals to implementation, moving from language theory to practical coding.

  • Includes multiple examples building from simple to more complex applications in four key areas: machine learning, visualization, vision recognition, and mobile computing
  • Addresses the foundational issues for CUDA development: multi-threaded programming and the different memory hierarchy
  • Includes teaching chapters designed to give a full understanding of CUDA tools, techniques and structure.
  • Presents CUDA techniques in the context of the hardware they are implemented on as well as other styles of programming that will help readers bridge into the new material

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Information

Publisher
Morgan Kaufmann
Year
2011
ISBN
9780123884329
Topic
Computer Science
Subtopic
Systems Architecture
Index
Computer Science

Table of contents

  1. Cover image
  2. Table of Contents
  3. Front Matter
  4. Copyright
  5. Dedication
  6. Foreword
  7. Preface
  8. Chapter 1. First Programs and How to Think in CUDA
  9. Chapter 2. CUDA for Machine Learning and Optimization
  10. Chapter 3. The CUDA Tool Suite
  11. Chapter 4. The CUDA Execution Model
  12. Chapter 5. CUDA Memory
  13. Chapter 6. Efficiently Using GPU Memory
  14. Chapter 7. Techniques to Increase Parallelism
  15. Chapter 8. CUDA for All GPU and CPU Applications
  16. Chapter 9. Mixing CUDA and Rendering
  17. Chapter 10. CUDA in a Cloud and Cluster Environments
  18. Chapter 11. CUDA for Real Problems
  19. Chapter 12. Application Focus on Live Streaming Video
  20. Works Cited
  21. Index