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CUDA Application Design and Development

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CUDA Application Design and Development Cover

 

Synopses & Reviews

Publisher Comments:

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

About the Author

Senior Scientist, Pacific Northwest National Laboratory

Senior Scientist, Pacific Northwest National Laboratory

Table of Contents

1. How to think in CUDA

2. Tools to build, debug and profile

3. The GPU performance envelope

4. The CUDA memory subsystems

5. Exploiting the CUDA execution grid

6. MultiGPU applications and scaling

7. Numerical CUDA, libraries and high-level language bindings

8. Mixing CUDA with rendering

9. High Performance Machine Learning

10. Scientific Visualization

11. Multimedia with OpenCV

12. Ultra Low-power Devices: Tegra

Product Details

ISBN:
9780123884268
Author:
Farber, Rob
Publisher:
Morgan Kaufmann Publishers
Subject:
General Computers
Subject:
Computer Architecture - General
Publication Date:
20111131
Binding:
TRADE PAPER
Language:
English
Pages:
400
Dimensions:
9.25 x 7.5 in

Related Subjects

Business » Investing
Computers and Internet » Computer Architecture » General
Computers and Internet » Computer Architecture » Parallel
Computers and Internet » Computers Reference » General
Computers and Internet » Operating Systems » General
Computers and Internet » Software Engineering » Programming and Languages
Health and Self-Help » Health and Medicine » Medical Specialties

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