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大规模并行处理器程序设计（英文版·原书第3版）
[美]大卫·B. 柯克 胡文美（Wen-mei W. Hwu
- 扉页
- Preface Acknowledgements+书签
- CHAPTER1 Introduction1
- 11 Heterogeneous Parallel Computing2
- 12 Architecture of a Modern GPU6
- 13 Why More Speed or Parallelism?8
- 14 Speeding Up Real Applications10
- 15 Challenges in Parallel Programming 12
- 16 Parallel Programming Languages and Models12
- 17 Overarching Goals14
- 18 Organization of the Book15
- References 18
- CHAPTER2 Data Parallel Computing19
- 21 Data Parallelism20
- 22 CUDA C Program Structure22
- 23 A Vector Addition Kernel 25
- 24 Device Global Memory and Data Transfer27
- 25 Kernel Functions and Threading32
- 26 Kernel Launch37
- 27 Summary38
- Function Declarations38
- Kernel Launch38
- Built-in (Predefined) Variables 39
- Run-time API39
- 28 Exercises39
- References 41
- CHAPTER3 Scalable Parallel Execution43
- 31 CUDA Thread Organization43
- 32 Mapping Threads to Multidimensional Data47
- 33 Image Blur: A More Complex Kernel 54
- 34 Synchronization and Transparent Scalability 58
- 35 Resource Assignment60
- 36 Querying Device Properties61
- 37 Thread Scheduling and Latency Tolerance64
- 38 Summary67
- 39 Exercises67
- CHAPTER4 Memory and Data Locality 71
- 41 Importance of Memory Access Efficiency72
- 42 Matrix Multiplication73
- 43 CUDA Memory Types77
- 44 Tiling for Reduced Memory Traffic84
- 45 A Tiled Matrix Multiplication Kernel90
- 46 Boundary Checks94
- 47 Memory as a Limiting Factor to Parallelism97
- 48 Summary99
- 49 Exercises
大规模并行处理器程序设计（英文版·原书第3版）
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