CUDA Application Design and Development

CUDA Application Design and Development

by Rob Farber
ISBN-10:
0123884268
ISBN-13:
9780123884268
Pub. Date:
10/31/2011
Publisher:
Elsevier Science
ISBN-10:
0123884268
ISBN-13:
9780123884268
Pub. Date:
10/31/2011
Publisher:
Elsevier Science
CUDA Application Design and Development

CUDA Application Design and Development

by Rob Farber
$49.95
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Overview

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.


Product Details

ISBN-13: 9780123884268
Publisher: Elsevier Science
Publication date: 10/31/2011
Pages: 336
Product dimensions: 7.46(w) x 9.18(h) x 0.82(d)

About the Author

Rob Farber has served as a scientist in Europe at the Irish Center for High-End Computing as well as U.S. national labs in Los Alamos, Berkeley, and the Pacific Northwest. He has also been on the external faculty at the Santa Fe Institute, consultant to fortune 100 companies, and co-founder of two computational startups that achieved liquidity events. He is the author of “CUDA Application Design and Development” as well as numerous articles and tutorials that have appeared in Dr. Dobb's Journal and Scientific Computing, The Code Project and others.

Table of Contents

1. First Programs and How to Think in CUDA

2. CUDA for Machine Learning and Optimization

3. The CUDA Tool Suite: Profiling a PCA/NLPCA Functor

4. The CUDA Execution Model

5. CUDA Memory

6. Efficiently Using GPU Memory

7. Techniques to Increase Parallelism

8. CUDA for All GPU and CPU Applications

9. Mixing CUDA and Rendering

10. CUDA in a Cloud and Cluster Environments

11. CUDA for Real Problems: Monte Carlo, Modeling, and More

12. Application Focus on Live Streaming Video

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A roadmap for developers facing the challenge of developing applications to effectively use GPUs with CUDA to achieve efficiency and performance goals

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