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Heterogeneous computing with OpenCL 2.0 /
Heterogeneous Computing with OpenCL 2.0 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). This fully-revised edition includes the latest enhancements in Open...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Waltham, MA :
Morgan Kaufmann,
[2015]
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| Edición: | Third edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Heterogeneous Computing with OpenCL 2.0; Copyright; Contents; List of Figures; List of Tables; Foreword; Acknowledgments; Chapter 1: Introduction; 1.1 Introduction to Heterogeneous Computing; 1.2 The Goals of This Book; 1.3 Thinking Parallel; 1.4 Concurrency and Parallel Programming Models; 1.5 Threads and Shared Memory; 1.6 Message-Passing Communication; 1.7 Different Grains of Parallelism; 1.7.1 Data Sharing and Synchronization; 1.7.2 Shared Virtual Memory; 1.8 Heterogeneous Computing with OpenCL; 1.9 Book Structure; References; Chapter 2: Device architectures; 2.1 Introduction
- 2.2 Hardware Trade-offs2.2.1 Performance Increase with Frequency, and its Limitations; 2.2.2 Superscalar Execution; 2.2.3 Very Long Instruction Word; 2.2.4 SIMD and Vector Processing; 2.2.5 Hardware Multithreading; 2.2.6 Multicore Architectures; 2.2.7 Integration: Systems-on-Chip and the APU; 2.2.8 Cache Hierarchies and Memory Systems; 2.3 The Architectural Design Space; 2.3.1 CPU Designs; Low-power CPUs; Mainstream desktop CPUs; Server CPUs; 2.3.2 GPU Architectures; Handheld GPUs; At the high end: AMD Radeon R9 290X and NVIDIA GeForce GTX 780; 2.3.3 APU and APU-like Designs; 2.4 Summary
- 3.6 The OpenCL Runtime with an Example3.6.1 Complete Vector Addition Listing; 3.7 Vector Addition Using an OpenCL C++ Wrapper; 3.8 OpenCL for CUDA Programmers; 3.9 Summary; Reference; Chapter 4: Examples; 4.1 OpenCL Examples; 4.2 Histogram; 4.3 Image Rotation; 4.4 Image Convolution; 4.5 Producer-Consumer; 4.6 Utility Functions; 4.6.1 Reporting Compilation Errors; 4.6.2 Creating a Program String; 4.7 Summary; Chapter 5: OpenCL runtime and concurrency model; 5.1 Commands and the Queuing Model; 5.1.1 Blocking Memory Operations; 5.1.2 Events; 5.1.3 Command Barriers and Markers
- 5.1.4 Event Callbacks5.1.5 Profiling Using Events; 5.1.6 User Events; 5.1.7 Out-of-Order Command-Queues; 5.2 Multiple Command-Queues; 5.3 The Kernel Execution Domain: Work-Items, Work-Groups, and NDRanges; 5.3.1 Synchronization; 5.3.2 Work-Group Barriers; 5.3.3 Built-In Work-Group Functions; 5.3.4 Predicate Evaluation Functions; 5.3.5 Broadcast Functions; 5.3.6 Parallel Primitive Functions; 5.4 Native and Built-In Kernels; 5.4.1 Native kernels; 5.4.2 Built-in kernels; 5.5 Device-Side Queuing; 5.5.1 Creating a Device-Side Queue; 5.5.2 Enqueuing Device-Side Kernels; Dynamic local memory