Programming a GPU with CUDA with sample programs.

1. Introduction to CUDAIn
-Narrative By
Winnie Thomas

2. CPU vs GPU

3. What is CUDA
• CUDA Architecture
– Expose GPU computing for general purpose
– Retain performance
• CUDA C/C++
– Based on industry-standard C/C++
– Small set of extensions to enable heterogeneous
programming.
– Straightforward APIs to manage devices, memory
etc.

4. Introduction to CUDA C/C++
• Start from Hello world
• Write a C code on GPU
• Manage GPU memory

5. Heterogeneous Computing
• Terminology:
– Host The CPU and its memory (host memory)
– Device The GPU and its memory (device memory)

6. Heterogeneous Computing

7. Simple Processing Flow

8. Simple Processing Flow

9. Simple Processing Flow

10. Hello World

11. Hello World with Device Code

12. Hello World with Device Code

13. Hello World with Device Code

14. Hello World with Device Code

15. Parallel Programming in CUDA C/C++

16. Addition on the Device

17. Addition on the Device

18. Memory Management

19. Addition on the Device : add()

20. Addition on the Device: main()

21. Addition on the Device: main()

22. Moving to Parallel

23. Vector Addition on Device

24. Vector Addition on Device

25. Vector Addition on Device: add()

26. Vector Addition on Device: main()

27. Vector Addition on Device: main()

28. Review

29. Review

30. CUDA Threads

31. Vector Addition Using Threads: main()

32. Vector Addition Using Threads: main()

33. Vector Addition Using Threads: main()

34. Combining threads and blocks

35. Indexing array with threads and blocks

36. Indexing array :example

37. Vector addition with blocks and
threads

38. Vector addition with blocks and
threads:main()

39. Vector addition with blocks and
threads:main()

40. ID and Dimensions