Heterogeneous computing with OpenCL
Heterogeneous Computing with OpenCL 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. Designed to work on multiple platforms an...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Boston :
Elsevier/MK
c2013.
|
| Edición: | Rev. OpenCL 1.2 ed |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628682906719 |
Tabla de Contenidos:
- Front Cover; Heterogeneous Computing with OpenCL; Copyright; Contents; 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; Threads and Shared Memory; Message-Passing Communication; Different Grains of Parallelism; Data Sharing and Synchronization; Structure; Reference; Further Reading and Relevant Websites
- Chapter 2: Introduction to OpenCL Introduction; The OpenCL Standard; The OpenCL Specification; Kernels and the OpenCL Execution Model; Platform and Devices; Host-Device Interaction; The Execution Environment; Contexts; Command Queues; Events; Memory Objects; Buffers; Images; Flush and Finish; Creating an OpenCL Program Object; The OpenCL Kernel; 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
- Performance Increase by Frequency, and Its Limitations Superscalar Execution; VLIW; SIMD and Vector Processing; Hardware Multithreading; Multi-Core Architectures; Integration: Systems-on-Chip and the APU; Cache Hierarchies and Memory Systems; The architectural design space; CPU Designs; Low-Power CPUs; Mainstream Desktop CPUs; Intel Itanium 2; Niagara; GPU Architectures; Handheld GPUs; At the High End: AMD Radeon HD7970 and NVIDIA GTX580; APU and APU-Like Designs; Summary; References; Chapter 4: Basic OpenCL Examples; Introduction; Example Applications; Simple Matrix Multiplication Example
- Step 1: Set Up Environment Step 2: Declare Buffers and Move Data; Step 3: Run time Kernel Compilation; Step 4: Run the Program; Step 5: Return Results to Host; Image Rotation Example; Step 1: Set Up Environment; Step 2: Declare Buffers and Move Data; Step 3: Run time Kernel Compilation; Step 4: Run the Program; Step 5: Read Result Back to Host; Image Convolution Example; Step 1: Create Image and Buffer Objects; Step 2: Write the Input Data; Step 3: Create Sampler Object; Step 4: Compile and Execute the Kernel; Step 5: Read the Result; The Convolution Kernel; 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; Memory Consistency in OpenCL; Events; Command Queues to Multiple Devices; Event Uses beyond Synchronization; User Events; Event Callbacks; Native Kernels; Command Barriers and Markers; The Host-Side Memory Model; Buffers; Manipulating Buffer Objects; Images; The Device-Side Memory Model; Device-Side Relaxed Consistency; Global Memory; Local Memory
- Constant Memory
