Book contents
- Frontmatter
- Dedication
- Contents
- Figures
- Tables
- Examples
- Preface
- 1 Introduction to GPU Kernels and Hardware
- 2 Thinking and Coding in Parallel
- 3 Warps and Cooperative Groups
- 4 Parallel Stencils
- 5 Textures
- 6 Monte Carlo Applications
- 7 Concurrency Using CUDA Streams and Events
- 8 Application to PET Scanners
- 9 Scaling Up
- 10 Tools for Profiling and Debugging
- 11 Tensor Cores
- Appendix A A Brief History of CUDA
- Appendix B Atomic Operations
- Appendix C The NVCC Compiler
- Appendix D AVX and the Intel Compiler
- Appendix E Number Formats
- Appendix F CUDA Documentation and Libraries
- Appendix G The CX Header Files
- Appendix H AI and Python
- Appendix I Topics in C++
- Index
Appendix A - A Brief History of CUDA
Published online by Cambridge University Press: 04 May 2022
Book contents
- Frontmatter
- Dedication
- Contents
- Figures
- Tables
- Examples
- Preface
- 1 Introduction to GPU Kernels and Hardware
- 2 Thinking and Coding in Parallel
- 3 Warps and Cooperative Groups
- 4 Parallel Stencils
- 5 Textures
- 6 Monte Carlo Applications
- 7 Concurrency Using CUDA Streams and Events
- 8 Application to PET Scanners
- 9 Scaling Up
- 10 Tools for Profiling and Debugging
- 11 Tensor Cores
- Appendix A A Brief History of CUDA
- Appendix B Atomic Operations
- Appendix C The NVCC Compiler
- Appendix D AVX and the Intel Compiler
- Appendix E Number Formats
- Appendix F CUDA Documentation and Libraries
- Appendix G The CX Header Files
- Appendix H AI and Python
- Appendix I Topics in C++
- Index
Summary
Appendix A provides a history of the evolution of NVIDIA GPUs and CUDA. It explains NVIDIA’s compute capability (CC) scheme for tracking the hardware capabilities for each GPU generation and discusses the evolution of CUDA software over successive releases of the CUDA SDK.
- Type
- Chapter
- Information
- Programming in Parallel with CUDAA Practical Guide, pp. 373 - 381Publisher: Cambridge University PressPrint publication year: 2022