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Classroom Contents
GPU Programming with Modern C++
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- 1 Introduction
- 2 Michaels background
- 3 Why Im here
- 4 Outline
- 5 Recap
- 6 Right abstraction
- 7 Task vs data parallelism
- 8 Latency and bandwidth
- 9 DMV example
- 10 Flynns Taxonomy
- 11 CPU vs GPU
- 12 Multicore CPU
- 13 Architectures
- 14 Memory bound problem
- 15 Memory optimization
- 16 Pad properly
- 17 Data layout
- 18 Power of computing
- 19 What happened
- 20 What happened in 2011
- 21 CPU vs GPU performance
- 22 GPU explosion
- 23 Hardware
- 24 GPU programming
- 25 Parallelization and concurrency
- 26 Heterogeneity
- 27 Consumer AI
- 28 GPU languages
- 29 C executives
- 30 How GPUs work
- 31 How CPUs work
- 32 How GPU work
- 33 Memory regions
- 34 Multiple work items
- 35 Wavefronts
- 36 Lockstep
- 37 Kernel barriers
- 38 Summary
- 39 Code
- 40 SpinD
- 41 ND Range
- 42 Sickle
- 43 Chronos
