Programming Massively Parallel Processors A Hands-On Approach |
|
| Author:
| Kirk, David B.
Hwu, Wen-Mei W. |
| ISBN: | 978-0-12-381473-9 |
| Publication Date: | Feb 2010 |
| Publisher: | Elsevier Science & Technology Books
|
| Imprint: | Morgan Kaufmann |
| Book Format: | Ebook |
| List Price: | USD $68.95USD $82.74 |
Book Description:
|
Programming Massively Parallel Processors discusses the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.
This book describes computational thinking techniques that will enable students to think about problems in ways that are amenable...
More Description
Programming Massively Parallel Processors discusses the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.
This book describes computational thinking techniques that will enable students to think about problems in ways that are amenable to high-performance parallel computing. It utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments. Studies learn how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL.
This book is recommended for advanced students, software engineers, programmers, and hardware engineers.
- Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing.
- Utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments.
- Shows you how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL.