Heterogeneous Computing with OpenCL

Heterogeneous Computing with OpenCL, Second Edition teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. It is the first textbook that presents OpenCL programming appropriate for the classroom and is intended to support a parallel programming course. Students will come away from this text with hands-on experience and significant knowledge of the syntax and use of OpenCL to address a range of fundamental parallel algorithms.

Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, Heterogeneous Computing with OpenCL explores memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. It includes detailed examples throughout, plus additional online exercises and other supporting materials that can be downloaded at http://www.heterogeneouscompute.org/?page_id=7

This book will appeal to software engineers, programmers, hardware engineers, and students/advanced students.

• Explains principles and strategies to learn parallel programming with OpenCL, from understanding the four abstraction models to thoroughly testing and debugging complete applications.
• Covers image processing, web plugins, particle simulations, video editing, performance optimization, and more.
• Shows how OpenCL maps to an example target architecture and explains some of the tradeoffs associated with mapping to various architectures
• Addresses a range of fundamental programming techniques, with multiple examples and case studies that demonstrate OpenCL extensions for a variety of hardware platforms

Software engineers, programmers, hardware engineers, students / advanced students

Foreword to the Revised OpenCL 1.2 Edition

Foreword to the First Edition

Preface

Our Heterogeneous World

OpenCL

This Text

Acknowledgments

About the Authors

Chapter 1. Introduction to Parallel Programming

Introduction

OpenCL

The Goals of This Book

Thinking Parallel

Concurrency and Parallel Programming Models

Structure

Reference

Further Reading and Relevant Websites

Chapter 2. Introduction to OpenCL

Introduction

Platform and Devices

The Execution Environment

Memory Model

Writing Kernels

Full Source Code Example for Vector Addition

Vector Addition with C++ Wrapper

Summary

Reference

Chapter 3. OpenCL Device Architectures

Introduction

Hardware trade-offs

The architectural design space

Summary

References

Chapter 4. Basic OpenCL Examples

Introduction

Example Applications

Compiling OpenCL Host Applications

Summary

Chapter 5. Understanding OpenCL’s Concurrency and Execution Model

Introduction

Kernels, Work-Items, Workgroups, and the Execution Domain

OpenCL Synchronization: Kernels, Fences, and Barriers

Queuing and Global Synchronization

The Host-Side Memory Model

The Device-Side Memory Model

Summary

Chapter 6. Dissecting a CPU/GPU OpenCL Implementation

Introduction

OpenCL on an AMD Bulldozer CPU

OpenCL on the AMD Radeon HD7970 GPU

Memory Performance Considerations in OpenCL

Summary

References

Chapter 7. Data Management

Memory management

Data transfer in a discrete environment

Data placement in a shared-memory environment

Example application—work group reduction

References

Chapter 8. OpenCL Case Study: Convolution

Introduction

Convolution Kernel

Conclusions

Code Listings

Reference

Chapter 9. OpenCL Case Study: Histogram

Introduction

Choosing the Number of Workgroups

Choosing the Optimal Workgroup Size

Optimizing Global Memory Data Access Patterns

Using Atomics to Perform Local Histogram

Optimizing Local Memory Access

Local Histogram Reduction

The Global Reduction

Full Kernel Code

Performance and Summary

Chapter 10. OpenCL Case Study: Mixed Particle Simulation

Introduction

Overview of the Computation

GPU Implementation

CPU Implementation

Load Balancing

Performance and Summary

Kernel for Uniform Grid Creation

Kernels for Simulation

Chapter 11. OpenCL Extensions

Introduction

Overview of Extension Mechanism

Device Fission

Double Precision

References

Chapter 12. Foreign Lands: Plugging OpenCL In

Introduction

Beyond C and C++

Haskell OpenCL

Summary

References

Chapter 13. OpenCL Profiling and Debugging

Introduction

Profiling with events

AMD Accelerated Parallel Processing Profiler

AMD Accelerated Parallel Processing KernelAnalyzer

Walking through the AMD APP Profiler

Debugging OpenCL Applications

Overview of gDEBugger

AMD Printf Extension

Conclusion

Chapter 14. Performance Optimization of an Image Analysis Application

Introduction

Description of the algorithm

Migrating multithreaded CPU implementation to OpenCL

Performance optimization

Power and performance analysis

Conclusion

References

Index