As part of the process of achieving the standards expected from an NVIDIA CUDA Professional Developer, all candidates are required to take a series of self-study lectures and exercises.

Please read this entire document before starting your study course.

The foundation of this training is provided by the text book,  Programming Massively Parallel Processors: A Hands-on Approach, authors, David B. Kirk, Wen-mei W. Hwu.

You can also make use of podcasts in mp4 format of the lectures below; the reading assignments will help to make the lecture more productive, so please complete in advance.

1. Introduction to GPU Computing (60.2 MB)
   1. Assignment please read Chapter 1 of Textbook
2. CUDA Programming Model (75.3 MB)
   1. Assignment please read Chapter 2 of Textbook
3. CUDA API (32.4 MB)
4. Simple Matrix Multiplication in CUDA (46.0 MB)
   1. Assignment please read Chapter 3 of Textbook
5. CUDA Memory Model (109 MB)
   1. Assignment please read Chapter 4 of Textbook
6. Shared Memory Matrix Multiplication (81.4 MB)
7. Additional CUDA API Features (22.4 MB)
8. Useful Information on CUDA Tools (15.7 MB)
9. Threading Hardware (140 MB)
   1. Assignment please read Chapter 5 of Textbook
10. Memory Hardware (85.8 MB)
11. Memory Bank Conflicts (115 MB)
12. Parallel Thread Execution (32.6 MB)
13. Control Flow (96.6 MB)
14. Precision (137 MB)
    1. Assignment please read Chapter 6 of Textbook
    2. Assignment please read Chapter 7 of Textbook

Please download all the documents and files that are relevant to your operating system.

As part of the study process, please ensure you also download and study the following documents:

CUDA C Programming Guide 3.0

CUDA C Best Practices Guide 3.0

CUDA C Online Documentation

Additional CUDA Programming Tools and Compiler Documentation can be found at this link:

www.nvidia.com/getcuda

Please download the following additional documents:

CUDA Compiler Driver NVCC 2.0

PTX: Parallel Thread Execution ISA Version 1.2

CUDA Occupancy Calculator

Additional Course Exercises with Solutions (Supports CUDA Basics)

Exercise Instructions

Exercise files for Visual Studio

Exercise files for Mac & Linux

Additional Supporting Materials

NVIDIA is hosting a series of Webinars about the CUDA Architecture.  NVIDIA staff is available during the presentations to answer questions, and the recordings are available for download.

www.nvidia.com/webinars

For technical questions please use the public CUDA developer forums:

http://forums.nvidia.com/index.php?showforum=62