CUDA Application Design and Development

Rob Farber

ISBN 10: 0123884268 / ISBN 13: 9780123884268

Published by Elsevier Inc Dez 2011, 2011

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 336 pp. Englisch.

Seller Inventory # 9780123884268

Bibliographic Details

• Title: CUDA Application Design and Development
• Publisher: Elsevier Inc Dez 2011
• Publication Date: 2011
• Language: English
• ISBN 10: 0123884268
• ISBN 13: 9780123884268
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 252W x 192H x 25D millimeters 252 millimeters width by 192 millimeters height by 25 millimeters depth
• Weight: 690 grams

About this title

Synopsis

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

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.