What: Intro to Parallel Programming is a free online course created by NVIDIA and Udacity. In this class you will learn the fundamentals of parallel computing using the CUDA parallel computing platform and programming model.
Who: This class is for developers, scientists, engineers, researchers and students who want to learn about GPU programming, algorithms, and optimization techniques.
Why: Learn new skills, enhance your career opportunities, and have fun.
How: Click on the Enroll Today button to get started!
Senior Director at NVIDIA Research
Read more about David:
homepage, twitter: @davedotluebke
Instructional Design Advisor
Assistant Professor at University of Colorado Denver
Adjunct Proefessor at University of Colorado Boulder
- Lesson 1 - GPU Programming Model
- Lesson 2 - GPU Hardware and Parallel Communication
- Lesson 3 - Fundamental Parallel Algorithms
- Lesson 4 - Using Sort and Scan
- Lesson 5 - Optimizing GPU Programs
- Lesson 6 - Parallel Computing Patterns
- Lesson 7 - The Future of GPU Computing
What level is this course?
This is an advanced course.
What are the pre-requisites?
Working knowledge of the C programming language, data structures and common algorithms.
How long will it take to complete the course?
Estimated time to complete course: 7 units x avg. of 3 hours each = Approx. 21 hours.
Do I need a CUDA-enabled computer?
No. You'll be able to program and run your assignments on high-end GPUs, via the Udacity system.
When does the course begin?
This class is self-paced. You can begin whenever you like.
How long will the course be available?
This class will always be available.
How much does this cost?
It’s completely free! If you’re feeling generous, we would love to have you contribute your thoughts, questions, and answers to the course discussion forum.
What are the rules on collaboration?
Collaboration is a great way to learn. The key is to use collaboration as a way to enhance learning, not as a way of sharing answers without understanding them.
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